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170 Program Highlights »
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Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #1
Equality of Opportunity in Classification: A Causal Approach
Junzhe Zhang · Elias Bareinboim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #2
Confounding-Robust Policy Improvement
Nathan Kallus · Angela Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #3
Causal Discovery from Discrete Data using Hidden Compact Representation
Ruichu Cai · Jie Qiao · Kun Zhang · Zhenjie Zhang · Zhifeng Hao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #4
Dirichlet belief networks for topic structure learning
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #5
Approximate Knowledge Compilation by Online Collapsed Importance Sampling
Tal Friedman · Guy Van den Broeck
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #6
Proximal Graphical Event Models
Debarun Bhattacharjya · Dharmashankar Subramanian · Tian Gao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #7
Dynamic Network Model from Partial Observations
Elahe Ghalebi · Baharan Mirzasoleiman · Radu Grosu · Jure Leskovec
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #8
HOGWILD!-Gibbs can be PanAccurate
Constantinos Daskalakis · Nishanth Dikkala · Siddhartha Jayanti
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #9
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #10
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues
Soumendu Sundar Mukherjee · Purnamrita Sarkar · Y. X. Rachel Wang · Bowei Yan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #11
Coupled Variational Bayes via Optimization Embedding
Bo Dai · Hanjun Dai · Niao He · Weiyang Liu · Zhen Liu · Jianshu Chen · Lin Xiao · Le Song
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #12
Stochastic Nonparametric Event-Tensor Decomposition
Shandian Zhe · Yishuai Du
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #13
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob Gardner · Geoff Pleiss · Kilian Weinberger · David Bindel · Andrew Wilson
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #14
Heterogeneous Multi-output Gaussian Process Prediction
Pablo Moreno-Muñoz · Antonio Artés · Mauricio Álvarez
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #15
Probabilistic Matrix Factorization for Automated Machine Learning
Nicolo Fusi · Rishit Sheth · Melih Elibol
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #16
Stochastic Expectation Maximization with Variance Reduction
Jianfei Chen · Jun Zhu · Yee Whye Teh · Tong Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #17
Generative Neural Machine Translation
Harshil Shah · David Barber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #18
Sparse Covariance Modeling in High Dimensions with Gaussian Processes
Rui Li · Kishan KC · Feng Cui · Justin Domke · Anne Haake
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #19
Variational Learning on Aggregate Outputs with Gaussian Processes
Ho Chung Law · Dino Sejdinovic · Ewan Cameron · Tim Lucas · Seth Flaxman · Katherine Battle · Kenji Fukumizu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #20
Learning Invariances using the Marginal Likelihood
Mark van der Wilk · Matthias Bauer · ST John · James Hensman
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #21
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios · Raffaello Camoriano · Pietro Michiardi · Lorenzo Rosasco · Maurizio Filippone
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #22
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang · Beomjoon Kim · Leslie Kaelbling
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #23
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
Mojmir Mutny · Andreas Krause
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #24
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic · Jonathan Scarlett · Stefanie Jegelka · Volkan Cevher
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #25
Multi-objective Maximization of Monotone Submodular Functions with Cardinality Constraint
Rajan Udwani
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #26
Variational PDEs for Acceleration on Manifolds and Application to Diffeomorphisms
Ganesh Sundaramoorthi · Anthony Yezzi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #27
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates
Krishnakumar Balasubramanian · Saeed Ghadimi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #28
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Soeren Laue · Matthias Mitterreiter · Joachim Giesen
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #29
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
Lei Wu · Chao Ma · Weinan E
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #30
The Effect of Network Width on the Performance of Large-batch Training
Lingjiao Chen · Hongyi Wang · Jinman Zhao · Dimitris Papailiopoulos · Paraschos Koutris
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #31
COLA: Decentralized Linear Learning
Lie He · An Bian · Martin Jaggi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #32
Distributed Stochastic Optimization via Adaptive SGD
Ashok Cutkosky · Róbert Busa-Fekete
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #33
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates
Quoc Tran Dinh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #34
Breaking the Span Assumption Yields Fast Finite-Sum Minimization
Robert Hannah · Yanli Liu · Daniel O'Connor · Wotao Yin
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #35
Optimization for Approximate Submodularity
Yaron Singer · Avinatan Hassidim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #36
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions
Wenruo Bai · William Stafford Noble · Jeff Bilmes
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #37
Maximizing Induced Cardinality Under a Determinantal Point Process
Jennifer Gillenwater · Alex Kulesza · Sergei Vassilvitskii · Zelda Mariet
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #38
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization
Francis Bach
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #39
Revisiting Decomposable Submodular Function Minimization with Incidence Relations
Pan Li · Olgica Milenkovic
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #40
Coordinate Descent with Bandit Sampling
Farnood Salehi · Patrick Thiran · Elisa Celis
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #41
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization
Robert Gower · Filip Hanzely · Peter Richtarik · Sebastian Stich
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #42
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni · Mitchell Stern · Chi Jin · Jeffrey Regier · Michael Jordan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #43
On the Local Minima of the Empirical Risk
Chi Jin · Lydia T. Liu · Rong Ge · Michael Jordan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #44
Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization
Dongruo Zhou · Pan Xu · Quanquan Gu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #45
NEON2: Finding Local Minima via First-Order Oracles
Zeyuan Allen-Zhu · Yuanzhi Li
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #46
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
Richard Zhang · Cedric Josz · Somayeh Sojoudi · Javad Lavaei
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #47
Escaping Saddle Points in Constrained Optimization
Aryan Mokhtari · Asuman Ozdaglar · Ali Jadbabaie
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #48
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
Yair Carmon · John Duchi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #49
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
Cong Fang · Chris Junchi Li · Zhouchen Lin · Tong Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #50
Natasha 2: Faster Non-Convex Optimization Than SGD
Zeyuan Allen-Zhu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #51
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu · Bhavya Kailkhura · Pin-Yu Chen · Paishun Ting · Shiyu Chang · Lisa Amini
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #52
Structured Local Minima in Sparse Blind Deconvolution
Yuqian Zhang · Han-wen Kuo · John Wright
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #53
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Simon Du · Wei Hu · Jason Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #54
Are ResNets Provably Better than Linear Predictors?
Ohad Shamir
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #55
Adaptive Methods for Nonconvex Optimization
Manzil Zaheer · Sashank Reddi · Devendra Sachan · Satyen Kale · Sanjiv Kumar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #56
Alternating optimization of decision trees, with application to learning sparse oblique trees
Miguel A. Carreira-Perpinan · Pooya Tavallali
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #57
GILBO: One Metric to Measure Them All
Alexander Alemi · Ian Fischer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #58
Isolating Sources of Disentanglement in Variational Autoencoders
Tian Qi Chen · Xuechen Li · Roger Grosse · David Duvenaud
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #59
On GANs and GMMs
Eitan Richardson · Yair Weiss
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #60
Assessing Generative Models via Precision and Recall
Mehdi S. M. Sajjadi · Olivier Bachem · Mario Lucic · Olivier Bousquet · Sylvain Gelly
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #61
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
Jie Hu · Li Shen · Samuel Albanie · Gang Sun · Andrea Vedaldi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #62
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo · Hae Beom Lee · Saehoon Kim · Juho Lee · Kwang Joon Kim · Eunho Yang · Sung Ju Hwang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #63
Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks
Bryan Lim · Ahmed M. Alaa · Mihaela van der Schaar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #64
Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming
Fei Wang · James Decker · Xilun Wu · Gregory Essertel · Tiark Rompf
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #65
Recurrent World Models Facilitate Policy Evolution
David Ha · Jürgen Schmidhuber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #66
Long short-term memory and Learning-to-learn in networks of spiking neurons
Guillaume Bellec · Darjan Salaj · Anand Subramoney · Robert Legenstein · Wolfgang Maass
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #67
Distributed Weight Consolidation: A Brain Segmentation Case Study
Patrick McClure · Charles Zheng · Jakub Kaczmarzyk · John Rogers-Lee · Satra Ghosh · Dylan Nielson · Peter A Bandettini · Francisco Pereira
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #68
Learning to Play With Intrinsically-Motivated, Self-Aware Agents
Nick Haber · Damian Mrowca · Stephanie Wang · Li Fei-Fei · Daniel Yamins
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #69
Gradient Descent for Spiking Neural Networks
Dongsung Huh · Terrence J Sejnowski
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #70
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation
Chaitanya Ryali · Gautam Reddy · Angela J Yu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #71
Temporal alignment and latent Gaussian process factor inference in population spike trains
Lea Duncker · Maneesh Sahani
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #72
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
Boyla Mainsah · Dmitry Kalika · Leslie Collins · Siyuan Liu · Chandra Throckmorton
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #73
Model-based targeted dimensionality reduction for neuronal population data
Mikio Aoi · Jonathan W Pillow
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #74
Objective and efficient inference for couplings in neuronal networks
Yu Terada · Tomoyuki Obuchi · Takuya Isomura · Yoshiyuki Kabashima
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #75
The emergence of multiple retinal cell types through efficient coding of natural movies
Samuel Ocko · Jack Lindsey · Surya Ganguli · Stephane Deny
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #76
Benefits of over-parameterization with EM
Ji Xu · Daniel Hsu · Arian Maleki
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #77
On Coresets for Logistic Regression
Alexander Munteanu · Chris Schwiegelshohn · Christian Sohler · David Woodruff
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #78
On Learning Markov Chains
Yi HAO · Alon Orlitsky · Venkatadheeraj Pichapati
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #79
Contextual Stochastic Block Models
Yash Deshpande · Subhabrata Sen · Andrea Montanari · Elchanan Mossel
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #80
Estimators for Multivariate Information Measures in General Probability Spaces
Arman Rahimzamani · Himanshu Asnani · Pramod Viswanath · Sreeram Kannan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #81
Blind Deconvolutional Phase Retrieval via Convex Programming
Ali Ahmed · Alireza Aghasi · Paul Hand
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #82
Entropy Rate Estimation for Markov Chains with Large State Space
Yanjun Han · Jiantao Jiao · Chuan-Zheng Lee · Tsachy Weissman · Yihong Wu · Tiancheng Yu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #83
Bandit Learning in Concave N-Person Games
Mario Bravo · David Leslie · Panayotis Mertikopoulos
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #84
Depth-Limited Solving for Imperfect-Information Games
Noam Brown · Tuomas Sandholm · Brandon Amos
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #85
The Physical Systems Behind Optimization Algorithms
Lin Yang · Raman Arora · Vladimir braverman · Tuo Zhao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #86
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
Jiantao Jiao · Weihao Gao · Yanjun Han
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #87
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng · Ilias Diakonikolas · Daniel Kane · Alistair Stewart
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #88
Information-theoretic Limits for Community Detection in Network Models
Chuyang Ke · Jean Honorio
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #89
Generalizing Graph Matching beyond Quadratic Assignment Model
Tianshu Yu · Junchi Yan · Yilin Wang · Wei Liu · baoxin Li
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #90
Improving Simple Models with Confidence Profiles
Amit Dhurandhar · Karthikeyan Shanmugam · Ronny Luss · Peder A Olsen
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #91
Online Learning with an Unknown Fairness Metric
Stephen Gillen · Christopher Jung · Michael Kearns · Aaron Roth
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #92
Legendre Decomposition for Tensors
Mahito Sugiyama · Hiroyuki Nakahara · Koji Tsuda
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #93
The Price of Privacy for Low-rank Factorization
Jalaj Upadhyay
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #94
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
Di Wang · Marco Gaboardi · Jinhui Xu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #95
Differentially Private Change-Point Detection
Sara Krehbiel · Rachel Cummings · Wanrong Zhang · Yajun Mei · Rui Tuo
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #96
Scalable Laplacian K-modes
Imtiaz Ziko · Eric Granger · Ismail Ben Ayed
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #97
Geometrically Coupled Monte Carlo Sampling
Mark Rowland · Krzysztof Choromanski · François Chalus · Aldo Pacchiano · Tamas Sarlos · Richard E Turner · Adrian Weller
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #98
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
Motoya Ohnishi · Masahiro Yukawa · Mikael Johansson · Masashi Sugiyama
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #99
Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization
Xiaoxuan Zhang · Mingrui Liu · Xun Zhou · Tianbao Yang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #100
Reducing Network Agnostophobia
Akshay Raj Dhamija · Manuel Günther · Terrance Boult
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #101
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Alessandro Achille · Tom Eccles · Loic Matthey · Chris Burgess · Nicholas Watters · Alexander Lerchner · Irina Higgins
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #102
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models
Yining Wang · Xi Chen · Yuan Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #103
The Everlasting Database: Statistical Validity at a Fair Price
Blake Woodworth · Vitaly Feldman · Saharon Rosset · Nati Srebro
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #104
Scalar Posterior Sampling with Applications
Georgios Theocharous · Zheng Wen · Yasin Abbasi · Nikos Vlassis
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #105
Iterative Value-Aware Model Learning
Amir-massoud Farahmand
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #106
A Lyapunov-based Approach to Safe Reinforcement Learning
Yinlam Chow · Ofir Nachum · Edgar Duenez-Guzman · Mohammad Ghavamzadeh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #107
Temporal Regularization for Markov Decision Process
Pierre Thodoroff · Audrey Durand · Joelle Pineau · Doina Precup
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #108
Maximum Causal Tsallis Entropy Imitation Learning
Kyungjae Lee · Sungjoon Choi · Songhwai Oh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #109
Policy Optimization via Importance Sampling
Alberto Maria Metelli · Matteo Papini · Francesco Faccio · Marcello Restelli
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #110
Reinforcement Learning of Theorem Proving
Cezary Kaliszyk · Josef Urban · Henryk Michalewski · Miroslav Olšák
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #111
Simple random search of static linear policies is competitive for reinforcement learning
Horia Mania · Aurelia Guy · Benjamin Recht
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #112
Meta-Gradient Reinforcement Learning
Zhongwen Xu · Hado van Hasselt · David Silver
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #113
Reinforcement Learning for Solving the Vehicle Routing Problem
MohammadReza Nazari · Afshin Oroojlooy · Lawrence Snyder · Martin Takac
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #114
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy · Matan Haroush · Nadav Merlis · Daniel J Mankowitz · Shie Mannor
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #115
REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis
Yu-Shao Peng · Kai-Fu Tang · Hsuan-Tien Lin · Edward Chang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #116
Learning Plannable Representations with Causal InfoGAN
Thanard Kurutach · Aviv Tamar · Ge Yang · Stuart Russell · Pieter Abbeel
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #117
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Edoardo Conti · Vashisht Madhavan · Felipe Petroski Such · Joel Lehman · Kenneth Stanley · Jeff Clune
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #118
Transfer of Deep Reactive Policies for MDP Planning
Aniket (Nick) Bajpai · Sankalp Garg · Mausam
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #119
Q-learning with Nearest Neighbors
Devavrat Shah · Qiaomin Xie
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #120
Distributed Multitask Reinforcement Learning with Quadratic Convergence
Rasul Tutunov · Dongho Kim · Haitham Bou Ammar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #121
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Qiang Liu · Lihong Li · Ziyang Tang · Dengyong Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #122
Constrained Cross-Entropy Method for Safe Reinforcement Learning
Min Wen · Ufuk Topcu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #123
Representation Balancing MDPs for Off-policy Policy Evaluation
Yao Liu · Omer Gottesman · Aniruddh Raghu · Matthieu Komorowski · Aldo A Faisal · Finale Doshi-Velez · Emma Brunskill
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #124
Dual Policy Iteration
Wen Sun · Geoffrey Gordon · Byron Boots · J. Bagnell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #125
Occam's razor is insufficient to infer the preferences of irrational agents
Stuart Armstrong · Sören Mindermann
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #126
Transfer of Value Functions via Variational Methods
Andrea Tirinzoni · Rafael Rodriguez Sanchez · Marcello Restelli
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #127
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach
Michael Gimelfarb · Scott Sanner · Chi-Guhn Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #128
Online Robust Policy Learning in the Presence of Unknown Adversaries
Aaron Havens · Zhanhong Jiang · Soumik Sarkar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #129
A Bayesian Approach to Generative Adversarial Imitation Learning
Wonseok Jeon · Seokin Seo · Kee-Eung Kim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #130
Verifiable Reinforcement Learning via Policy Extraction
Osbert Bastani · Yewen Pu · Armando Solar-Lezama
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #131
Deep Reinforcement Learning of Marked Temporal Point Processes
Utkarsh Upadhyay · Abir De · Manuel Gomez Rodriguez
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #132
On Learning Intrinsic Rewards for Policy Gradient Methods
Zeyu Zheng · Junhyuk Oh · Satinder Singh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #133
Evolution-Guided Policy Gradient in Reinforcement Learning
Shauharda Khadka · Kagan Tumer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #134
Meta-Reinforcement Learning of Structured Exploration Strategies
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #135
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Zhang-Wei Hong · Tzu-Yun Shann · Shih-Yang Su · Yi-Hsiang Chang · Tsu-Jui Fu · Chun-Yi Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #136
Genetic-Gated Networks for Deep Reinforcement Learning
Simyung Chang · John Yang · Jaeseok Choi · Nojun Kwak
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #137
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #138
Hardware Conditioned Policies for Multi-Robot Transfer Learning
Tao Chen · Adithyavairavan Murali · Abhinav Gupta
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #139
Reward learning from human preferences and demonstrations in Atari
Jan Leike · Borja Ibarz · Dario Amodei · Geoffrey Irving · Shane Legg
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #140
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You · Bowen Liu · Zhitao Ying · Vijay Pande · Jure Leskovec
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #141
Visual Reinforcement Learning with Imagined Goals
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #142
Playing hard exploration games by watching YouTube
Yusuf Aytar · Tobias Pfaff · David Budden · Thomas Paine · Ziyu Wang · Nando de Freitas
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #143
Unsupervised Video Object Segmentation for Deep Reinforcement Learning
Vikash Goel · Jameson Weng · Pascal Poupart
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #144
Learning to Navigate in Cities Without a Map
Piotr Mirowski · Matt Grimes · Mateusz Malinowski · Karl Moritz Hermann · Keith Anderson · Denis Teplyashin · Karen Simonyan · koray kavukcuoglu · Andrew Zisserman · Raia Hadsell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #145
Learning Abstract Options
Matthew Riemer · Miao Liu · Gerald Tesauro
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #146
Object-Oriented Dynamics Predictor
Guangxiang Zhu · Zhiao Huang · Chongjie Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #147
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents
YAN ZHENG · Zhaopeng Meng · Jianye Hao · Zongzhang Zhang · Tianpei Yang · Changjie Fan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #148
Learning Attentional Communication for Multi-Agent Cooperation
Jiechuan Jiang · Zongqing Lu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #149
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Jeremy Morton · Antony Jameson · Mykel J Kochenderfer · Freddie Witherden
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #150
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
Alexander Neitz · Giambattista Parascandolo · Stefan Bauer · Bernhard Schölkopf
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #151
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning
Ofir Marom · Benjamin Rosman
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #152
Total stochastic gradient algorithms and applications in reinforcement learning
Paavo Parmas
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #153
Fighting Boredom in Recommender Systems with Linear Reinforcement Learning
Romain WARLOP · Alessandro Lazaric · Jérémie Mary
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #154
Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband · John Aslanides · Albin Cassirer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #155
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou · Ian Osband · Benjamin Van Roy
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #156
Context-dependent upper-confidence bounds for directed exploration
Raksha Kumaraswamy · Matthew Schlegel · Adam White · Martha White
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #157
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song · Hongyu Ren · Dorsa Sadigh · Stefano Ermon
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #158
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Sriram Srinivasan · Marc Lanctot · Vinicius Zambaldi · Julien Perolat · Karl Tuyls · Remi Munos · Michael Bowling
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #159
Learning to Share and Hide Intentions using Information Regularization
Daniel Strouse · Max Kleiman-Weiner · Josh Tenenbaum · Matt Botvinick · David Schwab
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #160
Credit Assignment For Collective Multiagent RL With Global Rewards
Duc Thien Nguyen · Akshat Kumar · Hoong Chuin Lau
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #161
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
Hoi-To Wai · Zhuoran Yang · Princeton Zhaoran Wang · Mingyi Hong
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #162
Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs
Yanlin Han · Piotr Gmytrasiewicz
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #163
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments
Mahdi Imani · Seyede Fatemeh Ghoreishi · Ulisses M. Braga-Neto
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #164
Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making
Nishant Desai · Andrew Critch · Stuart J Russell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #165
rho-POMDPs have Lipschitz-Continuous epsilon-Optimal Value Functions
Mathieu Fehr · Olivier Buffet · Vincent Thomas · Jilles Dibangoye
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #166
Learning Task Specifications from Demonstrations
Marcell Vazquez-Chanlatte · Susmit Jha · Ashish Tiwari · Mark Ho · Sanjit Seshia
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #167
Teaching Inverse Reinforcement Learners via Features and Demonstrations
Luis Haug · Sebastian Tschiatschek · Adish Singla
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #168
Single-Agent Policy Tree Search With Guarantees
Laurent Orseau · Levi Lelis · Tor Lattimore · Theophane Weber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #169
From Stochastic Planning to Marginal MAP
Hao Cui · Radu Marinescu · Roni Khardon
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #170
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms
Zhihui Zhu · Yifan Wang · Daniel Robinson · Daniel Naiman · Rene Vidal · Manolis Tsakiris