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Break
Mon Dec 7th 08:00 - 09:30 AM @ 220 A
Breakfast
Tutorial
Mon Dec 7th 09:30 - 11:30 AM @ Level 2 room 210 E,F
Large-Scale Distributed Systems for Training Neural Networks
Jeff Dean · Oriol Vinyals
Tutorial
Mon Dec 7th 09:30 - 11:30 AM @ Level 2 room 210 AB
Deep Learning
Geoffrey E Hinton · Yoshua Bengio · Yann LeCun
Break
Mon Dec 7th 10:45 - 11:15 AM @ 210 C
Coffee Break
Tutorial
Mon Dec 7th 01:00 - 03:00 PM @ Level 2 room 210 AB
Monte Carlo Inference Methods
Iain Murray
Tutorial
Mon Dec 7th 01:00 - 03:00 PM @ Level 2 room 210 E,F
Probabilistic Programming
Frank Wood
Break
Mon Dec 7th 03:00 - 03:30 PM @ 210 C
Coffee Break
Tutorial
Mon Dec 7th 03:30 - 05:30 PM @ Level 2 room 210 E,F
High-Performance Hardware for Machine Learning
William Dally
Tutorial
Mon Dec 7th 03:30 - 05:30 PM @ Level 2 room 210 AB
Introduction to Reinforcement Learning with Function Approximation
Richard S Sutton
Session
Mon Dec 7th 06:30 - 06:55 PM @ 210 AB
Opening Remarks, Awards and Reception
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #1
Texture Synthesis Using Convolutional Neural Networks
Leon Gatys · Alexander S Ecker · Matthias Bethge
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #2
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling
Ming Liang · Xiaolin Hu · Bo Zhang
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #3
Grammar as a Foreign Language
Oriol Vinyals · Łukasz Kaiser · Terry Koo · Slav Petrov · Ilya Sutskever · Geoffrey Hinton
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #4
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction
Kisuk Lee · Aleks Zlateski · Vishwanathan Ashwin · H. Sebastian Seung
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #5
Generative Image Modeling Using Spatial LSTMs
Lucas Theis · Matthias Bethge
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #6
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren · Kaiming He · Ross Girshick · Jian Sun
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #7
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Jimei Yang · Scott E Reed · Ming-Hsuan Yang · Honglak Lee
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #8
Exploring Models and Data for Image Question Answering
Mengye Ren · Ryan Kiros · Richard Zemel
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #9
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
Haoyuan Gao · Junhua Mao · Jie Zhou · Zhiheng Huang · Lei Wang · Wei Xu
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #10
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
Marijn F Stollenga · Wonmin Byeon · Marcus Liwicki · Juergen Schmidhuber
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #11
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Özgür Şimşek · Marcus Buckmann
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #12
3D Object Proposals for Accurate Object Class Detection
Xiaozhi Chen · Kaustav Kundu · Yukun Zhu · Andrew G Berneshawi · Huimin Ma · Sanja Fidler · Raquel Urtasun
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #13
The Poisson Gamma Belief Network
Mingyuan Zhou · Yulai Cong · Bo Chen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #14
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data
Danilo Bzdok · Michael Eickenberg · Olivier Grisel · Bertrand Thirion · Gael Varoquaux
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #15
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux · Yoshua Bengio · Jean-Pierre David
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #16
Learning to Transduce with Unbounded Memory
Edward Grefenstette · Karl Moritz Hermann · Mustafa Suleyman · Phil Blunsom
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #17
Spectral Representations for Convolutional Neural Networks
Oren Rippel · Jasper Snoek · Ryan P Adams
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #18
A Theory of Decision Making Under Dynamic Context
Michael Shvartsman · Vaibhav Srivastava · Jonathan D Cohen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #19
Bidirectional Recurrent Neural Networks as Generative Models
Mathias Berglund · Tapani Raiko · Mikko Honkala · Leo Kärkkäinen · Akos Vetek · Juha T Karhunen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #20
Recognizing retinal ganglion cells in the dark
Emile Richard · Georges A Goetz · E. J. Chichilnisky
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #21
A Recurrent Latent Variable Model for Sequential Data
Junyoung Chung · Kyle Kastner · Laurent Dinh · Kratarth Goel · Aaron C Courville · Yoshua Bengio
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #22
Deep Knowledge Tracing
Chris Piech · Jonathan Bassen · Jonathan Huang · Surya Ganguli · Mehran Sahami · Leonidas J Guibas · Jascha Sohl-Dickstein
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #23
Deep Temporal Sigmoid Belief Networks for Sequence Modeling
Zhe Gan · Chunyuan Li · Ricardo Henao · David E Carlson · Lawrence Carin
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #24
Hidden Technical Debt in Machine Learning Systems
D. Sculley · Gary Holt · Daniel Golovin · Eugene Davydov · Todd Phillips · Dietmar Ebner · Vinay Chaudhary · Michael Young · JF Crespo · Dan Dennison
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #25
Statistical Model Criticism using Kernel Two Sample Tests
James R Lloyd · Zoubin Ghahramani
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #26
Calibrated Structured Prediction
Volodymyr Kuleshov · Percy S Liang
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #27
A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
Koosha Khalvati · Rajesh P Rao
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #28
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation
Scott Linderman · Matthew Johnson · Ryan P Adams
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #29
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models
Mike Hughes · Will T Stephenson · Erik Sudderth
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #30
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis
Ehsan Adeli-Mosabbeb · Kim-Han Thung · Le An · Feng Shi · Dinggang Shen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #31
Learning spatiotemporal trajectories from manifold-valued longitudinal data
Jean-Baptiste SCHIRATTI · Stéphanie ALLASSONNIERE · Olivier Colliot · Stanley DURRLEMAN
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #32
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
Minhyung Cho · Chandra Dhir · Jaehyung Lee
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #33
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
Amir Dezfouli · Edwin Bonilla · Edwin V Bonilla
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #34
Variational Dropout and the Local Reparameterization Trick
Diederik P Kingma · Tim Salimans · Max Welling
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #35
Infinite Factorial Dynamical Model
Isabel Valera · Francisco J. R. Ruiz · Lennart Svensson · Fernando Perez-Cruz
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #36
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
Shakir Mohamed · Danilo Jimenez Rezende
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #37
Copula variational inference
Dustin Tran · David Blei · Edo M Airoldi
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #38
Fast Second Order Stochastic Backpropagation for Variational Inference
Kai Fan · Ziteng Wang · Jeff Beck · James Kwok · Katherine A Heller
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #39
Rethinking LDA: Moment Matching for Discrete ICA
Anastasia Podosinnikova · Francis Bach · Simon Lacoste-Julien
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #40
Model-Based Relative Entropy Stochastic Search
Abbas Abdolmaleki · Rudolf Lioutikov · Jan R Peters · Nuno Lau · Luis Pualo Reis · Gerhard Neumann
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #41
Supervised Learning for Dynamical System Learning
Ahmed Hefny · Carlton Downey · Geoffrey J Gordon
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #42
Expectation Particle Belief Propagation
Thibaut Lienart · Yee Whye Teh · Arnaud Doucet
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #43
Embedding Inference for Structured Multilabel Prediction
Farzaneh Mirzazadeh · Siamak Ravanbakhsh · Nan Ding · Dale Schuurmans
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #44
Tractable Learning for Complex Probability Queries
Jessa Bekker · Jesse Davis · Arthur Choi · Adnan Darwiche · Guy Van den Broeck
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #45
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Nihar Bhadresh Shah · Denny Zhou
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #46
Local Expectation Gradients for Black Box Variational Inference
Michalis Titsias · Miguel Lázaro-Gredilla
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #47
Learning with a Wasserstein Loss
Charlie Frogner · Chiyuan Zhang · Hossein Mobahi · Mauricio Araya · Tomaso A Poggio
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #48
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
Vivien Seguy · Marco Cuturi
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #49
Fast and Accurate Inference of Plackett–Luce Models
Lucas Maystre · Matt Grossglauser
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #50
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
Dominik Rothenhäusler · Christina Heinze · Jonas Peters · Nicolai Meinshausen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #51
Learning with Relaxed Supervision
Jacob Steinhardt · Percy S Liang
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #52
M-Statistic for Kernel Change-Point Detection
Shuang Li · Yao Xie · Hanjun Dai · Le Song
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #53
Fast Two-Sample Testing with Analytic Representations of Probability Measures
Kacper P Chwialkowski · Aaditya Ramdas · Dino Sejdinovic · Arthur Gretton
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #54
Adversarial Prediction Games for Multivariate Losses
Hong Wang · Wei Xing · Kaiser Asif · Brian Ziebart
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #55
Regressive Virtual Metric Learning
Michaël Perrot · Amaury Habrard
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #56
Halting in Random Walk Kernels
Mahito Sugiyama · Karsten Borgwardt
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #57
Rate-Agnostic (Causal) Structure Learning
Sergey Plis · David Danks · Cynthia Freeman · Vince Calhoun
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #58
Online Prediction at the Limit of Zero Temperature
Mark Herbster · Stephen Pasteris · Shaona Ghosh
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #59
Lifted Symmetry Detection and Breaking for MAP Inference
Tim Kopp · Parag Singla · Henry Kautz
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #60
Bandits with Unobserved Confounders: A Causal Approach
Elias Bareinboim · Andrew Forney · Judea Pearl
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #61
Sample Complexity Bounds for Iterative Stochastic Policy Optimization
Marin Kobilarov
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #62
Basis refinement strategies for linear value function approximation in MDPs
Gheorghe Comanici · Doina Precup · Prakash Panangaden
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #63
Probabilistic Variational Bounds for Graphical Models
Qiang Liu · John W Fisher III · Alexander Ihler
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #64
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen · Nan Ding · Lawrence Carin
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #65
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
Xiao Li · Kannan Ramchandran
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #66
Discrete Rényi Classifiers
Meisam Razaviyayn · Farzan Farnia · David Tse
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #67
GAP Safe screening rules for sparse multi-task and multi-class models
Eugene Ndiaye · Olivier Fercoq · Alexandre Gramfort · Joseph Salmon
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #68
Decomposition Bounds for Marginal MAP
Wei Ping · Qiang Liu · Alexander Ihler
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #69
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
Kevin Scaman · Rémi Lemonnier · Nicolas Vayatis
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #70
Estimating Mixture Models via Mixtures of Polynomials
Sida Wang · Arun Tejasvi Chaganty · Percy S Liang
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #71
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
Eunho Yang · Aurelie C Lozano
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #72
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation
Alaa Saade · Florent Krzakala · Lenka Zdeborová
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #73
Robust PCA with compressed data
Wooseok Ha · Rina Foygel Barber
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #74
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications
Kai Wei · Rishabh K Iyer · Shengjie Wang · Wenruo Bai · Jeff A Bilmes
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #75
Subspace Clustering with Irrelevant Features via Robust Dantzig Selector
Chao Qu · Huan Xu
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #76
A class of network models recoverable by spectral clustering
Yali Wan · Marina Meila
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #77
Monotone k-Submodular Function Maximization with Size Constraints
Naoto Ohsaka · Yuichi Yoshida
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #78
Smooth and Strong: MAP Inference with Linear Convergence
Ofer Meshi · Mehrdad Mahdavi · Alex Schwing
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #79
StopWasting My Gradients: Practical SVRG
Reza Harikandeh · Mohamed Osama Ahmed · Alim Virani · Mark Schmidt · Jakub Konečný · Scott Sallinen
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #80
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction
Rakesh Shivanna · Bibaswan K Chatterjee · Raman Sankaran · Chiranjib Bhattacharyya · Francis Bach
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #81
Differentially Private Learning of Structured Discrete Distributions
Ilias Diakonikolas · Moritz Hardt · Ludwig Schmidt
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #82
Robust Portfolio Optimization
Huitong Qiu · Fang Han · Han Liu · Brian Caffo
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #83
Bayesian Optimization with Exponential Convergence
Kenji Kawaguchi · Leslie Kaelbling · Tomás Lozano-Pérez
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #84
Fast Randomized Kernel Ridge Regression with Statistical Guarantees
Ahmed Alaoui · Michael W Mahoney
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #85
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms
Christopher M De Sa · Ce Zhang · Kunle Olukotun · Christopher Ré · Chris Ré
Poster
Dates n/a. @ 210 C #86
Beyond Convexity: Stochastic Quasi-Convex Optimization
Elad Hazan · Kfir Levy · Shai Shalev-Shwartz
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #87
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors
Andrea Montanari · Daniel Reichman · Ofer Zeitouni
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #88
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees
Xinyang Yi · Constantine Caramanis
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #89
Black-box optimization of noisy functions with unknown smoothness
Jean-Bastien grill · Michal Valko · Remi Munos · Remi Munos
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #90
Combinatorial Cascading Bandits
Branislav Kveton · Zheng Wen · Azin Ashkan · Csaba Szepesvari
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #91
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
Tom Goldstein · Min Li · Xiaoming Yuan
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #92
Sum-of-Squares Lower Bounds for Sparse PCA
Tengyu Ma · Avi Wigderson
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #93
Online Gradient Boosting
Alina Beygelzimer · Elad Hazan · Satyen Kale · Haipeng Luo
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #94
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
Martin Slawski · Ping Li · Matthias Hein
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #95
Convergence Analysis of Prediction Markets via Randomized Subspace Descent
Rafael Frongillo · Mark D Reid
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #96
Accelerated Proximal Gradient Methods for Nonconvex Programming
Huan Li · Zhouchen Lin
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #97
Nearly Optimal Private LASSO
Kunal Talwar · Abhradeep Thakurta · Li Zhang
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #98
Minimax Time Series Prediction
Wouter M Koolen · Alan Malek · Peter L Bartlett · Yasin Abbasi
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #99
Communication Complexity of Distributed Convex Learning and Optimization
Yossi Arjevani · Ohad Shamir
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #100
Explore no more: Improved high-probability regret bounds for non-stochastic bandits
Gergely Neu
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #101
A Nonconvex Optimization Framework for Low Rank Matrix Estimation
Tuo Zhao · Zhaoran Wang · Han Liu
Poster
Mon Dec 7th 07:00 - 11:59 PM @ 210 C #102
Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability
Xia Qu · Prashant Doshi
Invited Talk (Posner Lecture)
Tue Dec 8th 09:00 - 09:50 AM @ Room 210 AB
Probabilistic Machine Learning: Foundations and Frontiers
Zoubin Ghahramani
Oral
Tue Dec 8th 09:50 - 10:10 AM @ Room 210 A
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco · Christopher Musco
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
Minimum Weight Perfect Matching via Blossom Belief Propagation
Sungsoo Ahn · Sung-Soo Ahn · Sejun Park · Misha Chertkov · Jinwoo Shin
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
Super-Resolution Off the Grid
Qingqing Huang · Sham Kakade
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
b-bit Marginal Regression
Martin Slawski · Ping Li
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
CHRISTOS THRAMPOULIDIS · Ehsan Abbasi · Babak Hassibi
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
Optimal Rates for Random Fourier Features
Bharath Sriperumbudur · Zoltan Szabo
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
Submodular Hamming Metrics
Jennifer Gillenwater · Rishabh K Iyer · Bethany Lusch · Rahul Kidambi · Jeff A Bilmes
Spotlight
Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A
Top-k Multiclass SVM
Maksim Lapin · Matthias Hein · Bernt Schiele
Break
Tue Dec 8th 10:35 - 10:55 AM @ 210 A
Coffee Break
Oral
Tue Dec 8th 10:55 - 11:35 AM @ Room 210 A
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Yuxin Chen · Emmanuel Candes
Oral
Tue Dec 8th 10:55 - 11:35 AM @ Room 210 A
Sampling from Probabilistic Submodular Models
Alkis Gotovos · Hamed Hassani · Andreas Krause
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Distributionally Robust Logistic Regression
Soroosh Shafieezadeh Abadeh · Peyman Esfahani · Daniel Kuhn
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
On some provably correct cases of variational inference for topic models
Pranjal Awasthi · Andrej Risteski
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Extending Gossip Algorithms to Distributed Estimation of U-statistics
Igor Colin · Aurélien Bellet · Joseph Salmon · Stéphan Clémençon
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
The Self-Normalized Estimator for Counterfactual Learning
Adith Swaminathan · Thorsten Joachims
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
François-Xavier Briol · Chris Oates · Mark Girolami · Michael A Osborne
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma
Murat A. Erdogdu
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian · Yijun Huang · Yuncheng Li · Ji Liu
Spotlight
Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Baharan Mirzasoleiman · Amin Karbasi · Ashwinkumar Badanidiyuru · Andreas Krause
Break
Tue Dec 8th 12:00 - 02:00 PM @ 210 A
Lunch Break
Invited Talk
Tue Dec 8th 02:00 - 02:50 PM @ Level 2 room 210 AB
Incremental Methods for Additive Cost Convex Optimization
Asuman Ozdaglar
Oral
Tue Dec 8th 02:50 - 03:30 PM @ Room 210 A
Probabilistic Line Searches for Stochastic Optimization
Maren Mahsereci · Philipp Hennig
Oral
Tue Dec 8th 02:50 - 03:30 PM @ Room 210 A
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
Mehrdad Farajtabar · Yichen Wang · Manuel Rodriguez · Shuang Li · Hongyuan Zha · Le Song
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Ryan J Giordano · Tamara Broderick · Michael I Jordan
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Latent Bayesian melding for integrating individual and population models
Mingjun Zhong · Nigel Goddard · Charles Sutton
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
Christopher M De Sa · Ce Zhang · Kunle Olukotun · Christopher Ré · Christopher Ré
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Automatic Variational Inference in Stan
Alp Kucukelbir · Rajesh Ranganath · Andrew Gelman · David Blei
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Data Generation as Sequential Decision Making
Philip Bachman · Doina Precup
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Stochastic Expectation Propagation
Yingzhen Li · José Miguel Hernández-Lobato · Richard E Turner
Spotlight
Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A
Deep learning with Elastic Averaging SGD
Sixin Zhang · Anna E Choromanska · Yann LeCun
Break
Tue Dec 8th 04:00 - 04:30 PM @ 210 A
Coffee Break
Oral
Tue Dec 8th 04:30 - 05:30 PM @ Room 210 A
Competitive Distribution Estimation: Why is Good-Turing Good
Alon Orlitsky · Ananda Theertha Suresh
Oral
Tue Dec 8th 04:30 - 05:30 PM @ Room 210 A
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis · Alekh Agarwal · Haipeng Luo · Robert Schapire
Oral
Tue Dec 8th 04:30 - 05:30 PM @ Room 210 A
Interactive Control of Diverse Complex Characters with Neural Networks
Igor Mordatch · Kendall Lowrey · Galen Andrew · Zoran Popovic · Emanuel Todorov
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
The Human Kernel
Andrew G Wilson · Christoph Dann · Chris Lucas · Eric P Xing
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
On the Pseudo-Dimension of Nearly Optimal Auctions
Jamie H Morgenstern · Tim Roughgarden
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
High-dimensional neural spike train analysis with generalized count linear dynamical systems
YUANJUN GAO · Lars Busing · Krishna V Shenoy · John Cunningham
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
Measuring Sample Quality with Stein's Method
Jackson Gorham · Lester Mackey
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
Biologically Inspired Dynamic Textures for Probing Motion Perception
Jonathan Vacher · Andrew Isaac Meso · Laurent U Perrinet · Gabriel Peyré
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
Piyush Rai · Changwei Hu · Ricardo Henao · Lawrence Carin
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
Closed-form Estimators for High-dimensional Generalized Linear Models
Eunho Yang · Aurelie C Lozano · Pradeep K Ravikumar
Spotlight
Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar · Thang Bui · Richard E Turner
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
Claudico: The World's Strongest No-Limit Texas Hold'em Poker AI
Noam Brown · Tuomas Sandholm
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
An interactive system for the extraction of meaningful visualizations from high-dimensional data
Madalina Fiterau · Artur Dubrawski · Donghan Wang
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
Deep Learning using Approximate Hardware
Joseph Bates
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
Fast sampling with neuromorphic hardware
Mihai A Petrovici · David Stöckel · Ilja Bytschok · Johannes Bill · Thomas Pfeil · Johannes Schemmel · Karlheinz Meier
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
Vitruvian Science: a visual editor for quickly building neural networks in the cloud
Markus Beissinger · Sherjil Ozair
Demonstration
Tue Dec 8th 07:00 - 11:55 PM @ 210D
DIANNE - Distributed Artificial Neural Networks
Steven Bohez · Tim Verbelen
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #1
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily L Denton · Soumith Chintala · arthur szlam · Rob Fergus
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #2
Shepard Convolutional Neural Networks
Jimmy SJ Ren · Li Xu · Qiong Yan · Wenxiu Sun
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #3
Learning Structured Output Representation using Deep Conditional Generative Models
Kihyuk Sohn · Honglak Lee · Xinchen Yan
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #4
Expressing an Image Stream with a Sequence of Natural Sentences
Cesc C Park · Gunhee Kim
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #5
Visalogy: Answering Visual Analogy Questions
Fereshteh Sadeghi · C. Lawrence Zitnick · Ali Farhadi
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #6
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution
Yan Huang · Wei Wang · Liang Wang
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #7
SubmodBoxes: Near-Optimal Search for a Set of Diverse Object Proposals
Qing Sun · Dhruv Batra
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #8
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning
Jiajun Wu · Ilker Yildirim · Joseph J Lim · Bill Freeman · Josh Tenenbaum
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #9
Learning visual biases from human imagination
Carl Vondrick · Hamed Pirsiavash · Aude Oliva · Antonio Torralba
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #10
Character-level Convolutional Networks for Text Classification
Xiang Zhang · Junbo Zhao · Yann LeCun
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #11
Winner-Take-All Autoencoders
Alireza Makhzani · Brendan J Frey
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #12
Learning both Weights and Connections for Efficient Neural Network
Song Han · Jeff Pool · John Tran · Bill Dally
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #13
Interactive Control of Diverse Complex Characters with Neural Networks
Igor Mordatch · Kendall Lowrey · Galen Andrew · Zoran Popovic · Emanuel Todorov
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #14
Biologically Inspired Dynamic Textures for Probing Motion Perception
Jonathan Vacher · Andrew Isaac Meso · Laurent U Perrinet · Gabriel Peyré
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #15
Unsupervised Learning by Program Synthesis
Kevin Ellis · Armando Solar-Lezama · Josh Tenenbaum
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #16
Deep Poisson Factor Modeling
Ricardo Henao · Zhe Gan · James Lu · Lawrence Carin
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #17
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
Piyush Rai · Changwei Hu · Ricardo Henao · Lawrence Carin
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #18
Tensorizing Neural Networks
Alexander Novikov · Dmitrii Podoprikhin · Anton Osokin · Dmitry P Vetrov
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #19
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy
Marylou Gabrie · Eric W Tramel · Florent Krzakala
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #20
The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions
Sebastian Bitzer · Stefan Kiebel
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #21
Unlocking neural population non-stationarities using hierarchical dynamics models
Mijung Park · Gergo Bohner · Jakob H Macke
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #22
Deeply Learning the Messages in Message Passing Inference
Guosheng Lin · Chunhua Shen · Ian Reid · Anton van den Hengel
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #23
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
Mehrdad Farajtabar · Yichen Wang · Manuel Rodriguez · Shuang Li · Hongyuan Zha · Le Song
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #24
The Human Kernel
Andrew G Wilson · Christoph Dann · Chris Lucas · Eric P Xing
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #25
Latent Bayesian melding for integrating individual and population models
Mingjun Zhong · Nigel Goddard · Charles Sutton
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #26
High-dimensional neural spike train analysis with generalized count linear dynamical systems
YUANJUN GAO · Lars Busing · Krishna V Shenoy · John Cunningham
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #27
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression
Yu-Ying Liu · Shuang Li · Fuxin Li · Le Song · James M Rehg
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #28
The Population Posterior and Bayesian Modeling on Streams
James McInerney · Rajesh Ranganath · David Blei
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #29
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Ye Wang · David B Dunson
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #30
Preconditioned Spectral Descent for Deep Learning
David E Carlson · Edo Collins · Ya-Ping Hsieh · Lawrence Carin · Volkan Cevher
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #31
Learning Continuous Control Policies by Stochastic Value Gradients
Nicolas Heess · Greg Wayne · David Silver · Tim Lillicrap · Tom Erez · Yuval Tassa
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #32
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar · Thang Bui · Richard E Turner
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #33
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Behnam Neyshabur · Russ R Salakhutdinov · Nati Srebro
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #34
Automatic Variational Inference in Stan
Alp Kucukelbir · Rajesh Ranganath · Andrew Gelman · David Blei
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #35
Data Generation as Sequential Decision Making
Philip Bachman · Doina Precup
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #36
Stochastic Expectation Propagation
Yingzhen Li · José Miguel Hernández-Lobato · Richard E Turner
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #37
Deep learning with Elastic Averaging SGD
Sixin Zhang · Anna E Choromanska · Yann LeCun
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #38
Learning with Group Invariant Features: A Kernel Perspective.
Youssef Mroueh · Stephen Voinea · Tomaso A Poggio
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #39
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Ryan J Giordano · Tamara Broderick · Michael I Jordan
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #40
Probabilistic Line Searches for Stochastic Optimization
Maren Mahsereci · Philipp Hennig
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #41
A hybrid sampler for Poisson-Kingman mixture models
Maria Lomeli · Stefano Favaro · Yee Whye Teh
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #42
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
Juho Lee · Seungjin Choi
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #43
Reflection, Refraction, and Hamiltonian Monte Carlo
Hadi Mohasel Afshar · Justin Domke
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #44
Planar Ultrametrics for Image Segmentation
Julian E Yarkony · Charless Fowlkes
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #45
Learning Bayesian Networks with Thousands of Variables
Mauro Scanagatta · Cassio P de Campos · Giorgio Corani · Marco Zaffalon
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #46
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah · Zoubin Ghahramani
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #47
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
Christopher M De Sa · Ce Zhang · Kunle Olukotun · Chris Ré
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #48
On some provably correct cases of variational inference for topic models
Pranjal Awasthi · Andrej Risteski
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #49
Large-scale probabilistic predictors with and without guarantees of validity
Vladimir Vovk · Ivan Petej · Valentina Fedorova
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #50
On the Accuracy of Self-Normalized Log-Linear Models
Jacob Andreas · Maxim Rabinovich · Michael I Jordan · Dan Klein
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #51
Policy Evaluation Using the Ω-Return
Philip S Thomas · Scott Niekum · Georgios Theocharous · George Konidaris
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #52
Community Detection via Measure Space Embedding
Mark Kozdoba · Shie Mannor
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #53
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels
Purnamrita Sarkar · Deepayan Chakrabarti · peter j bickel
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #54
Inference for determinantal point processes without spectral knowledge
Rémi Bardenet · Michalis Titsias
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #55
Sample Complexity of Learning Mahalanobis Distance Metrics
Nakul Verma · Kristin Branson
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #56
Matrix Manifold Optimization for Gaussian Mixtures
Reshad Hosseini · Suvrit Sra
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #57
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
François-Xavier Briol · Chris Oates · Mark Girolami · Michael A Osborne
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #58
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
Bo Xie · Yingyu Liang · Le Song
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #59
The Self-Normalized Estimator for Counterfactual Learning
Adith Swaminathan · Thorsten Joachims
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #60
Distributionally Robust Logistic Regression
Soroosh Shafieezadeh Abadeh · Peyman Esfahani · Daniel Kuhn
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #61
Top-k Multiclass SVM
Maksim Lapin · Matthias Hein · Bernt Schiele
Poster
Dates n/a. @ 210 C #62
Measuring Sample Quality with Stein's Method
Jackson Gorham · Lester Mackey
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #63
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian · Yijun Huang · Yuncheng Li · Ji Liu
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #64
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Yuxin Chen · Emmanuel Candes
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #65
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Baharan Mirzasoleiman · Amin Karbasi · Ashwinkumar Badanidiyuru · Andreas Krause
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #66
Parallel Correlation Clustering on Big Graphs
Xinghao Pan · Dimitris Papailiopoulos · Samet Oymak · Benjamin Recht · Kannan Ramchandran · Michael Jordan
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #67
Fast Bidirectional Probability Estimation in Markov Models
Sid Banerjee · Peter Lofgren
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #68
Evaluating the statistical significance of biclusters
Jason D Lee · Yuekai Sun · Jonathan E Taylor
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #69
Regularization Path of Cross-Validation Error Lower Bounds
Atsushi Shibagaki · Yoshiki Suzuki · Masayuki Karasuyama · Ichiro Takeuchi
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #70
Sampling from Probabilistic Submodular Models
Alkis Gotovos · Hamed Hassani · Andreas Krause
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #71
Submodular Hamming Metrics
Jennifer Gillenwater · Rishabh K Iyer · Bethany Lusch · Rahul Kidambi · Jeff A Bilmes
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #72
Extending Gossip Algorithms to Distributed Estimation of U-statistics
Igor Colin · Aurélien Bellet · Joseph Salmon · Stéphan Clémençon
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #73
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma
Murat A. Erdogdu
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #74
Collaboratively Learning Preferences from Ordinal Data
Sewoong Oh · Kiran K Thekumparampil · Jiaming Xu
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #75
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk
Guillaume Papa · Stéphan Clémençon · Aurélien Bellet
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #76
Alternating Minimization for Regression Problems with Vector-valued Outputs
Prateek Jain · Ambuj Tewari
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #77
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
Sashank J. Reddi · Ahmed Hefny · Suvrit Sra · Barnabas Poczos · Alex J Smola
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #78
Subset Selection by Pareto Optimization
Chao Qian · Yang Yu · Zhi-Hua Zhou
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #79
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm
Qinqing Zheng · Ryota Tomioka
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #80
Minimum Weight Perfect Matching via Blossom Belief Propagation
Sung-Soo Ahn · Sejun Park · Misha Chertkov · Jinwoo Shin
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #81
b-bit Marginal Regression
Martin Slawski · Ping Li
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #82
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
CHRISTOS THRAMPOULIDIS · Ehsan Abbasi · Babak Hassibi
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #83
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco · Christopher Musco
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #84
On the Pseudo-Dimension of Nearly Optimal Auctions
Jamie H Morgenstern · Tim Roughgarden
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #85
Closed-form Estimators for High-dimensional Generalized Linear Models
Eunho Yang · Aurelie C Lozano · Pradeep K Ravikumar
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #86
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
Rasmus Kyng · Anup Rao · Sushant Sachdeva
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #87
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
Niao He · Zaid Harchaoui
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #88
Competitive Distribution Estimation: Why is Good-Turing Good
Alon Orlitsky · Ananda Theertha Suresh
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #89
A Universal Primal-Dual Convex Optimization Framework
Alp Yurtsever · Quoc Tran Dinh · Volkan Cevher
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #90
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
Christoph Dann · Emma Brunskill
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #91
Private Graphon Estimation for Sparse Graphs
Christian Borgs · Jennifer Chayes · Adam Smith
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #92
HONOR: Hybrid Optimization for NOn-convex Regularized problems
Pinghua Gong · Jieping Ye
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #93
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
Qinqing Zheng · John Lafferty
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #94
Super-Resolution Off the Grid
Qingqing Huang · Sham Kakade
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #95
Optimal Rates for Random Fourier Features
Bharath Sriperumbudur · Zoltan Szabo
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #96
Combinatorial Bandits Revisited
Richard Combes · M. Sadegh Talebi · Alexandre Proutiere · marc lelarge
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #97
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis · Alekh Agarwal · Haipeng Luo · Robert Schapire
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #98
On Elicitation Complexity
Rafael Frongillo · Ian Kash
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #99
Online Learning with Adversarial Delays
Kent Quanrud · Daniel Khashabi
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #100
Structured Estimation with Atomic Norms: General Bounds and Applications
Sheng Chen · Arindam Banerjee
Poster
Tue Dec 8th 07:00 - 11:59 PM @ 210 C #101
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
Vitaly Feldman · Will Perkins · Santosh Vempala
Break
Wed Dec 9th 07:30 - 09:00 AM @ 220 A
Breakfast
Invited Talk (Breiman Lecture)
Wed Dec 9th 09:00 - 09:50 AM @ Level 2 room 210 AB
Post-selection Inference for Forward Stepwise Regression, Lasso and other Adaptive Statistical procedures
Robert Tibshirani
Oral
Wed Dec 9th 09:50 - 10:10 AM @ Room 210 A
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Vitaly Kuznetsov · Mehryar Mohri
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
Takashi Takenouchi · Takafumi Kanamori
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection
Jie Wang · Jieping Ye
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Optimal Testing for Properties of Distributions
Jayadev Acharya · Constantinos Daskalakis · Gautam C Kamath
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents
Mithun Chakraborty · Sanmay Das
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Information-theoretic lower bounds for convex optimization with erroneous oracles
Yaron Singer · Jan Vondrak
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
Ofer Dekel · Ronen Eldan · Tomer Koren
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Accelerated Mirror Descent in Continuous and Discrete Time
Walid Krichene · Alexandre Bayen · Peter L Bartlett
Spotlight
Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A
Adaptive Online Learning
Dylan J Foster · Alexander Rakhlin · Karthik Sridharan
Break
Wed Dec 9th 10:35 - 10:55 AM @ 210 A
Coffee Break
Oral
Wed Dec 9th 10:55 - 11:35 AM @ Room 210 A
Deep Visual Analogy-Making
Scott E Reed · Yi Zhang · Yuting Zhang · Honglak Lee
Oral
Wed Dec 9th 10:55 - 11:35 AM @ Room 210 A
End-To-End Memory Networks
Sainbayar Sukhbaatar · arthur szlam · Jason Weston · Rob Fergus
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Attention-Based Models for Speech Recognition
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Where are they looking?
Adria Recasens · Aditya Khosla · Carl Vondrick · Antonio Torralba
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Rie Johnson · Tong Zhang
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Training Very Deep Networks
Rupesh K Srivastava · Klaus Greff · Juergen Schmidhuber
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Deep Convolutional Inverse Graphics Network
Tejas D Kulkarni · William F. Whitney · Pushmeet Kohli · Josh Tenenbaum
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Learning to Segment Object Candidates
Pedro O Pinheiro · Ronan Collobert · Piotr Dollar
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors
Dan Rosenbaum · Yair Weiss
Spotlight
Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A
Spatial Transformer Networks
Max Jaderberg · Karen Simonyan · Andrew Zisserman · koray kavukcuoglu
Break
Wed Dec 9th 12:00 - 02:00 PM @ 210 A
Lunch Break
Invited Talk
Wed Dec 9th 02:00 - 02:50 PM @ Level 2 room 210 AB
Diagnosis and Therapy of Psychiatric Disorders Based on Brain Dynamics
Mitsuo Kawato
Oral
Wed Dec 9th 02:50 - 03:30 PM @ Room 210 A
A Reduced-Dimension fMRI Shared Response Model
Po-Hsuan (Cameron) Chen · Janice Chen · Yaara Yeshurun · Uri Hasson · James Haxby · Peter J Ramadge
Oral
Wed Dec 9th 02:50 - 03:30 PM @ Room 210 A
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments
Dane S Corneil · Wulfram Gerstner
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
Armand Joulin · Tomas Mikolov
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Seunghoon Hong · Hyeonwoo Noh · Bohyung Han
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
On-the-Job Learning with Bayesian Decision Theory
Keenon Werling · Arun Tejasvi Chaganty · Percy S Liang · Christopher Manning
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Learning Wake-Sleep Recurrent Attention Models
Jimmy Ba · Ruslan R Salakhutdinov · Roger B Grosse · Brendan J Frey
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Backpropagation for Energy-Efficient Neuromorphic Computing
Steve K Esser · Rathinakumar Appuswamy · Paul Merolla · John Arthur · Dharmendra S Modha
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
Yuval Harel · Ron Meir · Manfred Opper
Spotlight
Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A
Color Constancy by Learning to Predict Chromaticity from Luminance
Ayan Chakrabarti
Break
Wed Dec 9th 04:00 - 04:30 PM @ 210 A
Coffee Break
Invited Talk
Wed Dec 9th 04:30 - 05:20 PM @ Level 2 room 210 AB
Computational Principles for Deep Neuronal Architectures
Haim Sompolinsky
Oral
Wed Dec 9th 05:20 - 05:40 PM @ Room 210 A
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Pascal Vincent · Alexandre de Brébisson · Xavier Bouthillier
Spotlight
Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A
Pointer Networks
Oriol Vinyals · Meire Fortunato · Navdeep Jaitly
Spotlight
Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A
Precision-Recall-Gain Curves: PR Analysis Done Right
Peter Flach · Meelis Kull
Spotlight
Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
Kevin G Jamieson · Lalit Jain · Chris Fernandez · Nicholas J. Glattard · Rob Nowak
Spotlight
Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani · Tara Sainath · Sanjiv Kumar
Spotlight
Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A
Equilibrated adaptive learning rates for non-convex optimization
Yann Dauphin · Harm de Vries · Yoshua Bengio
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
Accelerated Deep Learning on GPUs: From Large Scale Training to Embedded Deployment
Allison Gray · Julie Bernauer
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
The pMMF multiresolution matrix factorization library
Risi Kondor · Pramod Kaushik Mudrakarta · Nedelina Teneva
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
Data-Driven Speech Animation
Yisong Yue · Iain Matthews
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
Scaling up visual search for product recommendation
Kevin Jing
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
Interactive Incremental Question Answering
Jordan L Boyd-Graber · Mohit Iyyer
Demonstration
Wed Dec 9th 07:00 - 11:55 PM @ 210D
CodaLab Worksheets for Reproducible, Executable Papers
Percy S Liang · Evelyne Viegas
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #1
Deep Visual Analogy-Making
Scott E Reed · Yi Zhang · Yuting Zhang · Honglak Lee
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #2
Where are they looking?
Adria Recasens · Aditya Khosla · Carl Vondrick · Antonio Torralba
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #3
Spatial Transformer Networks
Max Jaderberg · Karen Simonyan · Andrew Zisserman · koray kavukcuoglu
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #4
Training Very Deep Networks
Rupesh K Srivastava · Klaus Greff · Juergen Schmidhuber
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #5
Attention-Based Models for Speech Recognition
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #6
Deep Convolutional Inverse Graphics Network
Tejas D Kulkarni · William F. Whitney · Pushmeet Kohli · Josh Tenenbaum
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #7
End-To-End Memory Networks
Sainbayar Sukhbaatar · arthur szlam · Jason Weston · Rob Fergus
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #8
Learning to Segment Object Candidates
Pedro O Pinheiro · Ronan Collobert · Piotr Dollar
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #9
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
Armand Joulin · Tomas Mikolov
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #10
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments
Dane S Corneil · Wulfram Gerstner
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #11
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Rie Johnson · Tong Zhang
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #12
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors
Dan Rosenbaum · Yair Weiss
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #13
Backpropagation for Energy-Efficient Neuromorphic Computing
Steve K Esser · Rathinakumar Appuswamy · Paul Merolla · John Arthur · Dharmendra S Modha
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #14
Learning Wake-Sleep Recurrent Attention Models
Jimmy Ba · Russ R Salakhutdinov · Roger B Grosse · Brendan J Frey
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #15
On-the-Job Learning with Bayesian Decision Theory
Keenon Werling · Arun Tejasvi Chaganty · Percy S Liang · Chris Manning
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #16
Color Constancy by Learning to Predict Chromaticity from Luminance
Ayan Chakrabarti
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #17
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Seunghoon Hong · Hyeonwoo Noh · Bohyung Han
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #18
Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #19
Bayesian Active Model Selection with an Application to Automated Audiometry
Jacob Gardner · Gustavo Malkomes · Roman Garnett · Kilian Q Weinberger · Dennis Barbour · John Cunningham
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #20
Efficient and Robust Automated Machine Learning
Matthias Feurer · Aaron Klein · Katharina Eggensperger · Jost Springenberg · Manuel Blum · Frank Hutter
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #21
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure
Peter Schulam · Suchi Saria
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #22
Pointer Networks
Oriol Vinyals · Meire Fortunato · Navdeep Jaitly
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #23
A Reduced-Dimension fMRI Shared Response Model
Po-Hsuan (Cameron) Chen · Janice Chen · Yaara Yeshurun · Uri Hasson · James Haxby · Peter J Ramadge
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #24
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Pascal Vincent · Alexandre de Brébisson · Xavier Bouthillier
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #25
Precision-Recall-Gain Curves: PR Analysis Done Right
Peter Flach · Meelis Kull
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #26
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
Yuval Harel · Ron Meir · Manfred Opper
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #27
Equilibrated adaptive learning rates for non-convex optimization
Yann Dauphin · Harm de Vries · Yoshua Bengio
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #28
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
Kevin G Jamieson · Lalit Jain · Chris Fernandez · Nicholas J. Glattard · Rob Nowak
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #29
Gaussian Process Random Fields
Dave Moore · Stuart J Russell
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #30
MCMC for Variationally Sparse Gaussian Processes
James Hensman · Alexander G Matthews · Maurizio Filippone · Zoubin Ghahramani
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #31
Streaming, Distributed Variational Inference for Bayesian Nonparametrics
Trevor Campbell · Julian Straub · John W Fisher III · Jonathan P How
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #32
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
David I Inouye · Pradeep K Ravikumar · Inderjit S Dhillon
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #33
Human Memory Search as Initial-Visit Emitting Random Walk
Kwang-Sung Jun · Jerry Zhu · Timothy T Rogers · Zhuoran Yang · ming yuan
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #34
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani · Tara Sainath · Sanjiv Kumar
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #35
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
Chicheng Zhang · Jimin Song · Kamalika Chaudhuri · Kevin Chen
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #36
A Structural Smoothing Framework For Robust Graph Comparison
Pinar Yanardag · S.V.N. Vishwanathan
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #37
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
Ted Meeds · Max Welling
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #38
Inverse Reinforcement Learning with Locally Consistent Reward Functions
Quoc Phong Nguyen · Bryan Kian Hsiang Low · Patrick Jaillet
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #39
Consistent Multilabel Classification
Oluwasanmi Koyejo · Nagarajan Natarajan · Pradeep K Ravikumar · Inderjit S Dhillon
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #40
Is Approval Voting Optimal Given Approval Votes?
Ariel D Procaccia · Nisarg Shah
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #41
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan · Dmitri Chklovskii
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #42
Efficient Non-greedy Optimization of Decision Trees
Mohammad Norouzi · Maxwell Collins · Matthew A Johnson · David J Fleet · Pushmeet Kohli
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #43
Statistical Topological Data Analysis - A Kernel Perspective
Roland Kwitt · Stefan Huber · Marc Niethammer · Weili Lin · Ulrich Bauer
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #44
Variational Consensus Monte Carlo
Maxim Rabinovich · Elaine Angelino · Michael I Jordan
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #45
Softstar: Heuristic-Guided Probabilistic Inference
Mathew Monfort · Brenden M Lake · Brenden M Lake · Brian Ziebart · Patrick Lucey · Josh Tenenbaum
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #46
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
Heiko Strathmann · Dino Sejdinovic · Samuel Livingstone · Zoltan Szabo · Arthur Gretton
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #47
A Complete Recipe for Stochastic Gradient MCMC
Yi-An Ma · Tianqi Chen · Emily Fox
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #48
Barrier Frank-Wolfe for Marginal Inference
Rahul G Krishnan · Simon Lacoste-Julien · David Sontag
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #49
Practical and Optimal LSH for Angular Distance
Alexandr Andoni · Piotr Indyk · Thijs Laarhoven · Ilya Razenshteyn · Ludwig Schmidt
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #50
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Jonas W Mueller · Tommi Jaakkola
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #51
Kullback-Leibler Proximal Variational Inference
Mohammad E Khan · Pierre Baque · François Fleuret · Pascal Fua
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #52
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
Gunwoong Park · Garvesh Raskutti
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #53
Streaming Min-max Hypergraph Partitioning
Dan Alistarh · Jenny Iglesias · Milan Vojnovic
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #54
Efficient Output Kernel Learning for Multiple Tasks
Pratik Jawanpuria · Maksim Lapin · Matthias Hein · Bernt Schiele
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #55
Gradient Estimation Using Stochastic Computation Graphs
John Schulman · Nicolas Heess · Theophane Weber · Pieter Abbeel
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #56
Lifted Inference Rules With Constraints
Happy Mittal · Anuj Mahajan · Vibhav G Gogate · Parag Singla
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #57
Sparse PCA via Bipartite Matchings
Megasthenis Asteris · Dimitris Papailiopoulos · Tasos Kyrillidis · Alex Dimakis
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #58
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
Takashi Takenouchi · Takafumi Kanamori
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #59
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
Fredrik D Johansson · Ankani Chattoraj · Chiranjib Bhattacharyya · Devdatt Dubhashi
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #60
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
Balázs Szörényi · Róbert Busa-Fekete · Adil Paul · Eyke Hüllermeier
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #61
Segregated Graphs and Marginals of Chain Graph Models
Ilya Shpitser
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #62
Approximating Sparse PCA from Incomplete Data
ABHISEK KUNDU · Petros Drineas · Malik Magdon-Ismail
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #63
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection
Jie Wang · Jieping Ye
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #64
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters
Emmanuel Abbe · Colin Sandon
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #65
Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets
Justin Domke
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #66
Testing Closeness With Unequal Sized Samples
Bhaswar Bhattacharya · Gregory Valiant
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #67
Learning Causal Graphs with Small Interventions
Karthikeyan Shanmugam · Murat Kocaoglu · Alex Dimakis · Sriram Vishwanath
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #68
Regret-Based Pruning in Extensive-Form Games
Noam Brown · Tuomas Sandholm
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #69
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
Kirthevasan Kandasamy · Akshay Krishnamurthy · Barnabas Poczos · Larry Wasserman · james m robins
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #70
Bounding errors of Expectation-Propagation
Guillaume P Dehaene · Simon Barthelmé
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #71
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents
Mithun Chakraborty · Sanmay Das
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #72
Local Smoothness in Variance Reduced Optimization
Daniel Vainsencher · Han Liu · Tong Zhang
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #73
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
Zhaoran Wang · Quanquan Gu · Yang Ning · Han Liu
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #74
Associative Memory via a Sparse Recovery Model
Arya Mazumdar · Ankit Singh Rawat
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #75
Matrix Completion Under Monotonic Single Index Models
Ravi Sastry Ganti · Laura Balzano · Rebecca Willett
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #76
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
Ian En-Hsu Yen · Kai Zhong · Cho-Jui Hsieh · Pradeep K Ravikumar · Inderjit S Dhillon
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #77
Convergence rates of sub-sampled Newton methods
Murat A. Erdogdu · Andrea Montanari
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #78
Variance Reduced Stochastic Gradient Descent with Neighbors
Thomas Hofmann · Aurelien Lucchi · Simon Lacoste-Julien · Brian McWilliams
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #79
Non-convex Statistical Optimization for Sparse Tensor Graphical Model
Wei Sun · Zhaoran Wang · Han Liu · Guang Cheng
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #80
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Kamalika Chaudhuri · Sham Kakade · Praneeth Netrapalli · Sujay Sanghavi
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #81
When are Kalman-Filter Restless Bandits Indexable?
Christopher R Dance · Tomi Silander
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #82
Policy Gradient for Coherent Risk Measures
Aviv Tamar · Yinlam Chow · Mohammad Ghavamzadeh · Shie Mannor
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #83
A Dual Augmented Block Minimization Framework for Learning with Limited Memory
Ian En-Hsu Yen · Shan-Wei Lin · Shou-De Lin
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #84
On the Global Linear Convergence of Frank-Wolfe Optimization Variants
Simon Lacoste-Julien · Martin Jaggi
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #85
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
Zheng Qu · Peter Richtarik · Tong Zhang
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #86
A Generalization of Submodular Cover via the Diminishing Return Property on the Integer Lattice
Tasuku Soma · Yuichi Yoshida
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #87
A Universal Catalyst for First-Order Optimization
Hongzhou Lin · Julien Mairal · Zaid Harchaoui
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #88
Fast and Memory Optimal Low-Rank Matrix Approximation
Se-Young Yun · marc lelarge · Alexandre Proutiere
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #89
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
Tian Lin · Jian Li · Wei Chen
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #90
Linear Multi-Resource Allocation with Semi-Bandit Feedback
Tor Lattimore · Koby Crammer · Csaba Szepesvari
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #91
Exactness of Approximate MAP Inference in Continuous MRFs
Nicholas Ruozzi
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #92
On the consistency theory of high dimensional variable screening
Xiangyu Wang · Chenlei Leng · David B Dunson
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #93
Finite-Time Analysis of Projected Langevin Monte Carlo
Sebastien Bubeck · Ronen Eldan · Joseph Lehec
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #94
Optimal Testing for Properties of Distributions
Jayadev Acharya · Constantinos Daskalakis · Gautam C Kamath
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #95
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Vitaly Kuznetsov · Mehryar Mohri
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #96
Accelerated Mirror Descent in Continuous and Discrete Time
Walid Krichene · Alexandre Bayen · Peter L Bartlett
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #97
Information-theoretic lower bounds for convex optimization with erroneous oracles
Yaron Singer · Jan Vondrak
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #98
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
Ofer Dekel · Ronen Eldan · Tomer Koren
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #99
Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs
Vidyashankar Sivakumar · Arindam Banerjee · Pradeep K Ravikumar
Poster
Wed Dec 9th 07:00 - 11:59 PM @ 210 C #100
Adaptive Online Learning
Dylan J Foster · Alexander Rakhlin · Karthik Sridharan
Break
Thu Dec 10th 07:30 - 09:00 AM @ 220 A
Breakfast
Invited Talk (Posner Lecture)
Thu Dec 10th 09:00 - 09:50 AM @ Level 2 room 210 AB
Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer
Vladimir Vapnik
Oral
Thu Dec 10th 09:50 - 10:10 AM @ Room 210 A
Less is More: Nyström Computational Regularization
Alessandro Rudi · Raffaello Camoriano · Lorenzo Rosasco
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Logarithmic Time Online Multiclass prediction
Anna E Choromanska · John Langford
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Nikhil Rao · Hsiang-Fu Yu · Pradeep K Ravikumar · Inderjit S Dhillon
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Efficient and Parsimonious Agnostic Active Learning
Tzu-Kuo Huang · Alekh Agarwal · Daniel J Hsu · John Langford · Robert Schapire
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Matrix Completion with Noisy Side Information
Kai-Yang Chiang · Cho-Jui Hsieh · Inderjit S Dhillon
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen · Aditya Menon · Robert Williamson
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani · Yoav Freund
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Spherical Random Features for Polynomial Kernels
Jeffrey Pennington · Felix Yu · Sanjiv Kumar
Spotlight
Thu Dec 10th 10:10 - 10:40 AM @ Room 210 A
Fast and Guaranteed Tensor Decomposition via Sketching
Yining Wang · Hsiao-Yu Tung · Alex J Smola · Anima Anandkumar
Session
Thu Dec 10th 10:40 - 10:50 AM @ 210 A
Closing Remarks
Break
Thu Dec 10th 10:50 - 11:30 AM @ 210 A
Coffee Break
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #1
Teaching Machines to Read and Comprehend
Karl Moritz Hermann · Tomas Kocisky · Edward Grefenstette · Lasse Espeholt · Will Kay · Mustafa Suleyman · Phil Blunsom
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #2
Saliency, Scale and Information: Towards a Unifying Theory
Shafin Rahman · Neil Bruce
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #3
Semi-supervised Learning with Ladder Networks
Antti Rasmus · Mathias Berglund · Mikko Honkala · Harri Valpola · Tapani Raiko
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #4
Enforcing balance allows local supervised learning in spiking recurrent networks
Ralph Bourdoukan · Sophie Denève
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #5
Semi-supervised Sequence Learning
Andrew M Dai · Quoc V Le
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #6
Skip-Thought Vectors
Ryan Kiros · Yukun Zhu · Russ R Salakhutdinov · Richard Zemel · Raquel Urtasun · Antonio Torralba · Sanja Fidler
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #7
Learning to Linearize Under Uncertainty
Ross Goroshin · Michael F Mathieu · Yann LeCun
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #8
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring
David Kappel · Stefan Habenschuss · Robert Legenstein · Wolfgang Maass
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #9
Natural Neural Networks
Guillaume Desjardins · Karen Simonyan · Razvan Pascanu · koray kavukcuoglu
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #10
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David K Duvenaud · Dougal Maclaurin · Jorge Iparraguirre · Rafael Bombarell · Timothy Hirzel · Alan Aspuru-Guzik · Ryan P Adams
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #11
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian SHI · Zhourong Chen · Hao Wang · Dit-Yan Yeung · Wai-kin Wong · Wang-chun WOO
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #12
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio · Oriol Vinyals · Navdeep Jaitly · Noam Shazeer
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #13
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
Been Kim · Julie A Shah · Finale Doshi-Velez
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #14
Max-Margin Deep Generative Models
Chongxuan Li · Jun Zhu · Tianlin Shi · Bo Zhang
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #15
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions
Yuya Yoshikawa · Tomoharu Iwata · Hiroshi Sawada · Takeshi Yamada
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #16
A Gaussian Process Model of Quasar Spectral Energy Distributions
Andrew Miller · Albert Wu · Jeff Regier · Jon McAuliffe · Dustin Lang · Mr. Prabhat · David Schlegel · Ryan P Adams
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #17
Neural Adaptive Sequential Monte Carlo
Shixiang Gu · Zoubin Ghahramani · Richard E Turner
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #18
Convolutional spike-triggered covariance analysis for neural subunit models
Anqi Wu · Memming Park · Jonathan W Pillow
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #19
Rectified Factor Networks
Djork-Arné Clevert · Andreas Mayr · Thomas Unterthiner · Sepp Hochreiter
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #20
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter · Jost Springenberg · Joschka Boedecker · Martin Riedmiller
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #21
Bayesian dark knowledge
Anoop Korattikara Balan · Vivek Rathod · Kevin P Murphy · Max Welling
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #22
GP Kernels for Cross-Spectrum Analysis
Kyle R Ulrich · David E Carlson · Kafui Dzirasa · Lawrence Carin
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #23
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen · Ji He · Yelong Shen · Lin Xiao · Xiaodong He · Jianfeng Gao · Xinying Song · Li Deng
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #24
Particle Gibbs for Infinite Hidden Markov Models
Nilesh Tripuraneni · Shixiang Gu · Hong Ge · Zoubin Ghahramani
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #25
Sparse Local Embeddings for Extreme Multi-label Classification
Kush Bhatia · Himanshu Jain · Puru Kar · Manik Varma · Prateek Jain
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #26
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Moontae Lee · David Bindel · David Mimno
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #27
Space-Time Local Embeddings
Ke Sun · Jun Wang · Alexandros Kalousis · Stephane Marchand-Maillet
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #28
A fast, universal algorithm to learn parametric nonlinear embeddings
Miguel A. Carreira-Perpinan · Max Vladymyrov
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #29
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
Mijung Park · Wittawat Jitkrittum · Ahmad Qamar · Zoltan Szabo · Lars Buesing · Maneesh Sahani
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #30
Local Causal Discovery of Direct Causes and Effects
Tian Gao · Qiang Ji
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #31
Discriminative Robust Transformation Learning
Jiaji Huang · Qiang Qiu · Guillermo Sapiro · Robert Calderbank
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #32
Max-Margin Majority Voting for Learning from Crowds
TIAN TIAN · Jun Zhu
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #33
M-Best-Diverse Labelings for Submodular Energies and Beyond
Alexander Kirillov · Dmytro Shlezinger · Dmitry P Vetrov · Carsten Rother · Bogdan Savchynskyy
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #34
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
Xiaocheng Shang · Zhanxing Zhu · Benedict Leimkuhler · Amos J Storkey
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #35
Time-Sensitive Recommendation From Recurrent User Activities
Nan Du · Yichen Wang · Niao He · Jimeng Sun · Le Song
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #36
Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models
Akihiro Kishimoto · Radu Marinescu · Adi Botea
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #37
Logarithmic Time Online Multiclass prediction
Anna E Choromanska · John Langford
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #38
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani · Yoav Freund
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #39
Bounding the Cost of Search-Based Lifted Inference
David B Smith · Vibhav G Gogate
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #40
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction
Joseph Wang · Kirill Trapeznikov · Venkatesh Saligrama
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #41
Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach
Wenye Li
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #42
Sample Efficient Path Integral Control under Uncertainty
Yunpeng Pan · Evangelos Theodorou · Michail Kontitsis
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #43
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation
Jaya Kawale · Hung H Bui · Branislav Kveton · Long Tran-Thanh · Sanjay Chawla
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #44
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang · Richard Guo · Katherine Heller · David B Dunson
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #45
Fast Lifted MAP Inference via Partitioning
Somdeb Sarkhel · Parag Singla · Vibhav G Gogate
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #46
Active Learning from Weak and Strong Labelers
Chicheng Zhang · Kamalika Chaudhuri
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #47
Fast and Guaranteed Tensor Decomposition via Sketching
Yining Wang · Hsiao-Yu Tung · Alex J Smola · Anima Anandkumar
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #48
Spherical Random Features for Polynomial Kernels
Jeffrey Pennington · Felix Yu · Sanjiv Kumar
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #49
Learnability of Influence in Networks
Harikrishna Narasimhan · David C Parkes · Yaron Singer
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #50
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
James R Voss · Mikhail Belkin · Luis Rademacher
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #51
Differentially private subspace clustering
Yining Wang · Yu-Xiang Wang · Aarti Singh
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #52
Compressive spectral embedding: sidestepping the SVD
Dinesh Ramasamy · Upamanyu Madhow
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #53
Generalization in Adaptive Data Analysis and Holdout Reuse
Cynthia Dwork · Vitaly Feldman · Moritz Hardt · Toni Pitassi · Omer Reingold · Aaron Roth
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #54
Online F-Measure Optimization
Róbert Busa-Fekete · Balázs Szörényi · Krzysztof Dembczynski · Eyke Hüllermeier
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #55
Matrix Completion with Noisy Side Information
Kai-Yang Chiang · Cho-Jui Hsieh · Inderjit S Dhillon
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #56
A Market Framework for Eliciting Private Data
Bo Waggoner · Rafael Frongillo · Jacob D Abernethy
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #57
Optimal Ridge Detection using Coverage Risk
Yen-Chi Chen · Christopher Genovese · Shirley Ho · Larry Wasserman
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #58
Fast Distributed k-Center Clustering with Outliers on Massive Data
Gustavo Malkomes · Matt J Kusner · Wenlin Chen · Kilian Q Weinberger · Benjamin Moseley
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #59
Orthogonal NMF through Subspace Exploration
Megasthenis Asteris · Dimitris Papailiopoulos · Alex Dimakis
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #60
Fast Classification Rates for High-dimensional Gaussian Generative Models
Tianyang Li · Adarsh Prasad · Pradeep K Ravikumar
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #61
Efficient and Parsimonious Agnostic Active Learning
T.-K. Huang · Alekh Agarwal · Daniel J Hsu · John Langford · Robert Schapire
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #62
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Nikhil Rao · Hsiang-Fu Yu · Pradeep K Ravikumar · Inderjit S Dhillon
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #63
Less is More: Nyström Computational Regularization
Alessandro Rudi · Raffaello Camoriano · Lorenzo Rosasco
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #64
Predtron: A Family of Online Algorithms for General Prediction Problems
Prateek Jain · Nagarajan Natarajan · Ambuj Tewari
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #65
On the Optimality of Classifier Chain for Multi-label Classification
Weiwei Liu · Ivor Tsang
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #66
Smooth Interactive Submodular Set Cover
Bryan D He · Yisong Yue
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #67
Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number
Janne H Korhonen · Pekka Parviainen
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #68
Secure Multi-party Differential Privacy
Peter Kairouz · Sewoong Oh · Pramod Viswanath
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #69
Adaptive Stochastic Optimization: From Sets to Paths
Zhan Wei Lim · David Hsu · Wee Sun Lee
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #70
Learning structured densities via infinite dimensional exponential families
Siqi Sun · mladen kolar · Jinbo Xu
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #71
Lifelong Learning with Non-i.i.d. Tasks
Anastasia Pentina · Christoph H Lampert
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #72
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen · Aditya Menon · Robert Williamson
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #73
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
Huasen Wu · R. Srikant · Xin Liu · Chong Jiang
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #74
From random walks to distances on unweighted graphs
Tatsunori Hashimoto · Yi Sun · Tommi Jaakkola
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #75
Robust Regression via Hard Thresholding
Kush Bhatia · Prateek Jain · Puru Kar
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #76
Column Selection via Adaptive Sampling
Saurabh Paul · Malik Magdon-Ismail · Petros Drineas
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #77
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms
Yunwen Lei · Urun Dogan · Alexander Binder · Marius Kloft
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #78
Optimal Linear Estimation under Unknown Nonlinear Transform
Xinyang Yi · Zhaoran Wang · Constantine Caramanis · Han Liu
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #79
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Yinlam Chow · Aviv Tamar · Shie Mannor · Marco Pavone
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #80
Learning with Incremental Iterative Regularization
Lorenzo Rosasco · Silvia Villa
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #81
No-Regret Learning in Bayesian Games
Jason Hartline · Vasilis Syrgkanis · Eva Tardos
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #82
Sparse and Low-Rank Tensor Decomposition
Parikshit Shah · Nikhil Rao · Gongguo Tang
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #83
Analysis of Robust PCA via Local Incoherence
Huishuai Zhang · Yi Zhou · Yingbin Liang
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #84
Algorithmic Stability and Uniform Generalization
Ibrahim M Alabdulmohsin
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #85
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path
Daniel J Hsu · Aryeh Kontorovich · Csaba Szepesvari
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #86
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
Sohail Bahmani · Justin Romberg
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #87
Unified View of Matrix Completion under General Structural Constraints
Suriya Gunasekar · Arindam Banerjee · Joydeep Ghosh
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #88
Copeland Dueling Bandits
Masrour Zoghi · Zohar S Karnin · Shimon Whiteson · Maarten de Rijke
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #89
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Junpei Komiyama · Junya Honda · Hiroshi Nakagawa
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #90
Online Learning for Adversaries with Memory: Price of Past Mistakes
Oren Anava · Elad Hazan · Shie Mannor
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #91
Revenue Optimization against Strategic Buyers
Mehryar Mohri · Andres Munoz
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #92
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
Wei Cao · Jian Li · Yufei Tao · Zhize Li
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #93
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems
Ruoyu Sun · Mingyi Hong
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #94
Cornering Stationary and Restless Mixing Bandits with Remix-UCB
Julien Audiffren · Liva Ralaivola
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #95
Fighting Bandits with a New Kind of Smoothness
Jacob D Abernethy · Chansoo Lee · Ambuj Tewari
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #96
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
Sorathan Chaturapruek · John C Duchi · Chris Ré
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #97
The Pareto Regret Frontier for Bandits
Tor Lattimore
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #98
Online Learning with Gaussian Payoffs and Side Observations
Yifan Wu · András György · Csaba Szepesvari
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #99
Fast Rates for Exp-concave Empirical Risk Minimization
Tomer Koren · Kfir Levy
Poster
Thu Dec 10th 11:00 AM - 03:00 PM @ 210 C #100
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models
Theodoros Tsiligkaridis · Theodoros Tsiligkaridis · Keith Forsythe
Symposium
Thu Dec 10th 03:00 - 09:00 PM @ 210 a,b Level 2
Deep Learning Symposium
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng
Symposium
Thu Dec 10th 03:00 - 09:00 PM @ 210 e, f Level 2
Algorithms Among Us: the Societal Impacts of Machine Learning
Michael A Osborne · Adrian Weller · Murray Shanahan
Symposium
Thu Dec 10th 03:00 - 09:00 PM @ Level 5 Room 510 BD
Brains, Minds and Machines
Gabriel Kreiman · Tomaso A Poggio · Maximilian Nickel
Break
Thu Dec 10th 04:15 - 04:45 PM @
Coffee Break
Break
Thu Dec 10th 06:00 - 07:00 PM @ 220A
Hors d'oeuvres
Break
Fri Dec 11th 07:30 - 09:00 AM @ 220 A
Breakfast
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 512 cg
Cognitive Computation: Integrating neural and symbolic approaches
Artur Garcez · Tarek R. Besold · Risto Miikkulainen · Gary Marcus
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 b
Machine Learning for Spoken Language Understanding and Interactions
Asli Celikyilmaz · Milica Gasic · Dilek Hakkani-Tur
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 514 a
Adaptive Data Analysis
Adam Smith · Aaron Roth · Vitaly Feldman · Moritz Hardt
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 d
Learning Faster from Easy Data II
Tim van Erven · Wouter M Koolen
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 f
Statistical Methods for Understanding Neural Systems
Alyson Fletcher · Jakob H Macke · Ryan P Adams · Jascha Sohl-Dickstein
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 512 bf
Bounded Optimality and Rational Metareasoning
Samuel J Gershman · Falk Lieder · Tom Griffiths · Noah Goodman
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 512 dh
Multimodal Machine Learning
Louis-Philippe Morency · Tadas Baltrusaitis · Aaron Courville · Kyunghyun Cho
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ Room 515 a
Machine Learning and Interpretation in Neuroimaging (day 1)
Irina Rish · Leila Wehbe · Brian Murphy · Georg Langs · Guillermo Cecchi · Moritz Grosse-Wentrup
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 513 cd
Deep Reinforcement Learning
Pieter Abbeel · John Schulman · Satinder Singh · David Silver
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 c
Nonparametric Methods for Large Scale Representation Learning
Andrew G Wilson · Alex J Smola · Eric P Xing
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 510 ac
Optimization for Machine Learning (OPT2015)
Suvrit Sra · Alekh Agarwal · Leon Bottou · Sashank J. Reddi
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 513 ab
Advances in Approximate Bayesian Inference
Dustin Tran · Tamara Broderick · Stephan Mandt · James McInerney · Shakir Mohamed · Alp Kucukelbir · Matthew D Hoffman · Neil Lawrence · David Blei
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 512 e
Machine Learning for (e-)Commerce
Esteban Arcaute · Mohammad Ghavamzadeh · Shie Mannor · Georgios Theocharous
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 e
Modelling and inference for dynamics on complex interaction networks: joining up machine learning and statistical physics
Manfred Opper · Yasser Roudi · Peter Sollich
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 511 a
ABC in Montreal
Ted Meeds · Michael Gutmann · Dennis Prangle · Jean-Michel Marin · Richard Everitt
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 515 bc
Applying (machine) Learning to Experimental Physics (ALEPH) and «Flavours of Physics» challenge
Pavel Serdyukov · Andrey Ustyuzhanin · Marcin Chrząszcz · Francesco Dettori · Marc-Olivier Bettler
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 513 ef
The 1st International Workshop "Feature Extraction: Modern Questions and Challenges"
Dmitry Storcheus · Sanjiv Kumar · Afshin Rostamizadeh
Workshop
Fri Dec 11th 08:30 AM -- 06:30 PM @ 514 bc
Time Series Workshop
Oren Anava · Azadeh Khaleghi · Vitaly Kuznetsov · Alexander Rakhlin
Break
Fri Dec 11th 10:00 - 10:30 AM @ Foyer - 5th floor
Coffee Break
Break
Fri Dec 11th 04:00 - 04:30 PM @ Foyer - 5th floor
Coffee Break
Break
Sat Dec 12th 07:30 - 09:00 AM @ 220 A
Breakfast
Workshop
Sat Dec 12th 08:00 AM -- 06:30 PM @ 511 f
Extreme Classification 2015: Multi-class and Multi-label Learning in Extremely Large Label Spaces
Manik Varma · Moustapha M Cisse
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 512 cg
Cognitive Computation: Integrating neural and symbolic approaches (day 2)
Artur Garcez · Tarek R. Besold · Risto Miikkulainen · Gary Marcus
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 513 ab
Scalable Monte Carlo Methods for Bayesian Analysis of Big Data
Babak Shahbaba · Yee Whye Teh · Max Welling · Arnaud Doucet · Christophe Andrieu · Sebastian J. Vollmer · Pierre Jacob
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 514 bc
Transfer and Multi-Task Learning: Trends and New Perspectives
Anastasia Pentina · Christoph H Lampert · Sinno Jialin Pan · Mingsheng Long · Judy Hoffman · Baochen Sun · Kate Saenko
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 510 bd
Machine Learning in Computational Biology
Nicolo Fusi · Anna Goldenberg · Sara Mostafavi · Gerald Quon · Oliver Stegle
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ Room 515 a
Machine Learning and Interpretation in Neuroimaging (day 2)
Irina Rish · Leila Wehbe · Brian Murphy · Georg Langs · Guillermo Cecchi · Moritz Grosse-Wentrup
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 512 bf
Networks in the Social and Information Sciences
Edo M Airoldi · David S Choi · Aaron Clauset · Johan Ugander · Panagiotis Toulis
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 510 ac
Reasoning, Attention, Memory (RAM) Workshop
Jason E Weston · Sumit Chopra · Antoine Bordes
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 512 a
Quantum Machine Learning
Nathan Wiebe · Seth Lloyd
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 514 a
Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization
Joseph Jay Williams · Yasin Abbasi · Finale Doshi-Velez
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 511 e
BigNeuro 2015: Making sense of big neural data
Eva L Dyer · Joshua T Vogelstein · Konrad Koerding · Jeremy Freeman · Andreas S. Tolias
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 513 cd
Non-convex Optimization for Machine Learning: Theory and Practice
Anima Anandkumar · Niranjan Uma Naresh · Kamalika Chaudhuri · Percy S Liang · Sewoong Oh
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 512 e
Challenges in Machine Learning (CiML 2015): "Open Innovation" and "Coopetitions"
Isabelle Guyon · Evelyne Viegas · Ben Hamner · Balázs Kégl
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 513 ef
Black box learning and inference
Josh Tenenbaum · Jan-Willem van de Meent · Tejas D Kulkarni · S. M. Ali Eslami · Brooks Paige · Frank Wood · Zoubin Ghahramani
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 515 bc
Bayesian Nonparametrics: The Next Generation
Tamara Broderick · Nick Foti · Aaron Schein · Alex Tank · Hanna Wallach · Sinead A Williamson
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 511 d
Machine Learning Systems
Alex Beutel · Tianqi Chen · Sameer Singh · Elaine Angelino · Markus Weimer · Joseph E Gonzalez
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 511 b
Bayesian Optimization: Scalability and Flexibility
Bobak Shahriari · Ryan P Adams · Nando de Freitas · Amar Shah · Roberto Calandra
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 512 dh
Learning and privacy with incomplete data and weak supervision
Giorgio Patrini · Tony Jebara · Richard Nock · Dimitrios Kotzias · Xinnan Yu
Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 511 a
Learning, Inference and Control of Multi-Agent Systems
Vicenç Gómez · Gerhard Neumann · Jonathan S Yedidia · Peter H Stone
Break
Sat Dec 12th 10:00 - 10:30 AM @ Foyer - 5th floor
Coffee Break
Break
Sat Dec 12th 04:00 - 04:30 PM @ Foyer - 5th floor
Coffee Break
Break
Sat Dec 12th 07:00 - 11:00 PM @ 210
Banquet