NIPS : Conferences : 2011 : Program

Accepted Papers

$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding
C. Li, A. Saxena, T. Chen
A blind sparse deconvolution method for neural spike identification
C. Ekanadham, D. Tranchina, E. Simoncelli
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm
J. Dethier, P. Nuyujukian, C. Eliasmith, T. Stewart, S. Elasaad, K. Shenoy, K. Boahen
Accelerated Adaptive Markov Chain for Partition Function Computation
S. Ermon, C. Gomes, A. Sabharwal, B. Selman
A Collaborative Mechanism for Crowdsourcing Prediction Problems
J. Abernethy, R. Frongillo
A concave regularization technique for sparse mixture models
M. Larsson, J. Ugander
A Convergence Analysis of Log-Linear Training
S. Wiesler, H. Ney
Action-Gap Phenomenon in Reinforcement Learning
A. Farahmand
Active Classification based on Value of Classifier
T. Gao, D. Koller
Active dendrites: adaptation to spike-based communication
B. Ujfalussy, M. Lengyel
Active learning of neural response functions with Gaussian processes
M. Park, G. Horwitz, J. Pillow
Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity
N. Ailon
Active Learning with a Drifting Distribution
L. Yang
Active Ranking using Pairwise Comparisons
K. Jamieson, R. Nowak
Adaptive Hedge
T. van Erven, P. Grunwald, W. Koolen, S. Rooij
Additive Gaussian Processes
D. Duvenaud, H. Nickisch, C. Rasmussen
A Denoising View of Matrix Completion
W. Wang, M. Carreira-Perpinan, Z. Lu
Advice Refinement in Knowledge-Based SVMs
G. Kunapuli, R. Maclin, J. Shavlik
A Global Structural EM Algorithm for a Model of Cancer Progression
A. Tofigh, E. Sj̦lund, M. H̦glund, J. Lagergren
Agnostic Selective Classification
Y. Wiener, R. El-Yaniv
Algorithms and hardness results for parallel large margin learning
R. Servedio, P. Long
Algorithms for Hyper-Parameter Optimization
J. Bergstra, R. Bardenet, Y. Bengio, B. Kégl
A Machine Learning Approach to Predict Chemical Reactions
M. Kayala, P. Baldi
A Maximum Margin Multi-Instance Learning Framework for Image Categorization
H. Wang, H. Huang, F. Kamangar, F. Nie, C. Ding
A Model for Temporal Dependencies in Event Streams
A. Gunawardana, C. Meek, P. Xu
A More Powerful Two-Sample Test in High Dimensions using Random Projection
M. Lopes, L. Jacob, M. Wainwright
A Multilinear Subspace Regression Method Using Orthogonal Tensors Decompositions
Q. Zhao, C. Caiafa, D. Mandic, L. Zhang, T. Ball, A. Schulze-bonhage, A. CICHOCKI
Analysis and Improvement of Policy Gradient Estimation
T. Zhao, H. Hachiya, G. Niu, M. Sugiyama
Analytical Results for the Error in Filtering of Gaussian Processes
A. Susemihl, R. Meir, M. Opper
An Application of Tree-Structured Expectation Propagation for Channel Decoding
P. Olmos, L. Salamanca, J. Murillo Fuentes, F. Perez-Cruz
An Empirical Evaluation of Thompson Sampling
O. Chapelle, L. Li
An Exact Algorithm for F-Measure Maximization
K. Dembczynski, W. Waegeman, W. Cheng, E. Hullermeier
An ideal observer model for identifying the reference frame of objects
J. Austerweil, A. Friesen, T. Griffiths
A Non-Parametric Approach to Dynamic Programming
O. Kroemer, J. Peters
An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments
M. Mozer, B. Link, H. Pashler
Approximating Semidefinite Programs in Sublinear Time
D. Garber, E. Hazan
A rational model of causal inference with continuous causes
M. Pacer, T. Griffiths
A Reinforcement Learning Theory for Homeostatic Regulation
M. Keramati, B. Gutkin
A reinterpretation of the policy oscillation phenomenon in approximate policy iteration
P. Wagner
A Two-Stage Weighting Framework for Multi-Source Domain Adaptation
Q. Sun, R. Chattopadhyay, S. Panchanathan, J. Ye
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints
O. Khan, P. Poupart, J. Agosta
Autonomous Learning of Action Models for Planning
N. Mehta, P. Tadepalli, A. Fern
Bayesian Bias Mitigation for Crowdsourcing
F. Wauthier, M. Jordan
Bayesian Partitioning of Large-Scale Distance Data
D. Adametz, V. Roth
Bayesian Spike-Triggered Covariance Analysis
I. Park, J. Pillow
Beating SGD: Learning SVMs in Sublinear Time
E. Hazan, T. Koren, N. Srebro
Better Mini-Batch Algorithms via Accelerated Gradient Methods
A. Cotter, O. Shamir, N. Srebro, K. Sridharan
Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts
M. Hein, S. Setzer
Blending Autonomous Exploration and Apprenticeship Learning
T. Walsh, D. Hewlett, C. Morrison
Boosting with Maximum Adaptive Sampling
C. Dubout, F. Fleuret
Budgeted Optimization with Concurrent Stochastic-Duration Experiments
J. Azimi, A. Fern, X. Fern
Causal Discovery with Cyclic Additive Noise Models
J. Mooij, D. Janzing, T. Heskes, B. Schölkopf
Clustered Multi-Task Learning Via Alternating Structure Optimization
J. Zhou, J. Chen, J. Ye
Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery
S. Niekum, A. Barto
Co-regularized Multi-view Spectral Clustering
A. Kumar, P. Rai, H. Daume III
Co-Training for Domain Adaptation
M. Chen, K. Weinberger, J. Blitzer
Collective Graphical Models
D. Sheldon, T. Dietterich
Committing Bandits
L. Bui, R. Johari, S. Mannor
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs
A. Allahverdyan, A. Galstyan
Complexity of Inference in Latent Dirichlet Allocation
D. Sontag, D. Roy
Composite Multiclass Losses
E. Vernet, R. Williamson, M. Reid
Confidence Sets for Network Structure
D. Choi, P. Wolfe, E. Airoldi
Contextual Gaussian Process Bandit Optimization
A. Krause, C. Ong
Continuous-Time Regression Models for Longitudinal Networks
D. Vu, A. Asuncion, D. Hunter, P. Smyth
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
M. Schmidt, N. Le Roux, F. Bach
Convergent Bounds on the Euclidean Distance
Y. Hwang, H. Ahn
Convergent Fitted Value Iteration with Linear Function Approximation
D. Lizotte
Crowdclustering
R. Gomes, P. Welinder, A. Krause, P. Perona
Data Skeletonization via Reeb Graphs
X. Ge, I. Safa, M. Belkin, Y. Wang
Decoding of Finger Flexion from Electrocorticographic Signals Using Switching Non-Parametric Dynamic Systems
Z. Wang, G. Schalk, Q. Ji
Demixed Principal Component Analysis
W. Brendel, R. Romo, C. Machens
Differentially Private M-Estimators
J. Lei
Dimensionality Reduction Using the Sparse Linear Model
I. Gkioulekas, T. Zickler
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators
D. Perrault-Joncas, M. Meila
Distributed Delayed Stochastic Optimization
A. Agarwal, J. Duchi
Divide-and-Conquer Matrix Factorization
L. Mackey, A. Talwalkar, M. Jordan
Dynamical segmentation of single trials from population neural data
B. Petreska, B. Yu, J. Cunningham, G. Santhanam, S. Ryu, K. Shenoy, M. Sahani
Efficient anomaly detection using bipartite k-NN graphs
K. Sricharan, A. Hero
Efficient coding with a population of Linear-Nonlinear neurons
y. karklin, E. Simoncelli
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
P. Krähenbühl, V. Koltun
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression
S. Kakade, A. Kalai, V. Kanade, O. Shamir
Efficient Methods for Overlapping Group Lasso
L. Yuan, J. Liu, J. Ye
Efficient Offline Communication Policies for Factored Multiagent POMDPs
J. Messias, M. Spaan, P. Lima
Efficient Online Learning via Randomized Rounding
N. Cesa-Bianchi, O. Shamir
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning
Y. Qi, F. Yan
Emergence of Multiplication in a Biophysical Model of a Wide-Field Visual Neuron for Computing Object Approaches: Dynamics, Peaks, & Fits
M. Keil
Empirical models of spiking in neural populations
J. Macke, L. Buesing, J. Cunningham, B. Yu, K. Shenoy, M. Sahani
Energetically Optimal Action Potentials
M. Stemmler, B. Sengupta, S. Laughlin, J. Niven
Environmental statistics and the trade-off between model-based and TD learning in humans
D. Simon, N. Daw
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron
R. Kobayashi, Y. Tsubo, P. Lansky, S. Shinomoto
Evaluating computational models of preference learning
A. Jern, C. Lucas, C. Kemp
Exploiting spatial overlap to efficiently compute appearance distances between image windows
B. Alexe, V. Petrescu, V. Ferrari
Expressive Power and Approximation Errors of Restricted Boltzmann Machines
G. Montufar, J. Rauh, N. Ay
Extracting Speaker-Specific Information with a Regularized Siamese Deep Network
K. Chen, A. Salman
Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines
M. Zeiler, G. Taylor, L. Sigal, I. Matthews, R. Fergus
Fast and Accurate k-means For Large Datasets
M. Shindler, A. Wong, A. Meyerson
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition
J. Deng, S. Satheesh, A. Berg, F. Li
Fast approximate submodular minimization
S. Jegelka, H. Lin, J. Bilmes
Finite Time Analysis of Stratified Sampling for Monte Carlo
A. Carpentier, R. Munos
From Bandits to Experts: On the Value of Side-Observations
S. Mannor, O. Shamir
From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models
S. Mensi, R. Naud, W. Gerstner
Gaussian process modulated renewal processes
V. Rao, Y. Teh
Gaussian Process Training with Input Noise
A. McHutchon, C. Rasmussen
Generalised Coupled Tensor Factorisation
K. Yılmaz, A. Cemgil, U. Simsekli
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss
D. Mcallester, J. Keshet
Generalized Beta Mixtures of Gaussians
A. Armagan, D. Dunson, M. Clyde
Generalized Lasso based Approximation of Sparse Coding for Visual Recognition
N. Morioka, S. Satoh
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample
G. Blanchard, G. Lee, C. Scott
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent
S. Nakajima, M. Sugiyama, S. Babacan
Greedy Algorithms for Structurally Constrained High Dimensional Problems
A. Tewari, P. Ravikumar, I. Dhillon
Greedy Model Averaging
D. Dai, T. Zhang
Group Anomaly Detection using Flexible Genre Models
L. Xiong, B. Poczos, J. Schneider
Hashing Algorithms for Large-Scale Learning
P. Li, A. Shrivastava, J. Moore, A. König
Heavy-tailed Distances for Gradient Based Image Descriptors
Y. Jia, T. Darrell
Hierarchically Supervised Latent Dirichlet Allocation
A. Perotte, F. Wood, N. Elhadad, N. Bartlett
Hierarchical Matching Pursuit for Recognition: Architecture and Fast Algorithms
L. Bo, X. Ren, D. Fox
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation
N. Goernitz, C. Widmer, G. Zeller, A. Kahles, S. Sonnenburg, G. Raetsch
Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices
X. Zhang, D. Dunson, L. Carin
High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions
A. Anandkumar, V. Tan, A. Willsky
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity
P. Loh, M. Wainwright
Higher-Order Correlation Clustering for Image Segmentation
S. Kim, S. Nowozin, P. Kohli, C. Yoo
History distribution matching method for predicting effectiveness of HIV combination therapies
J. Bogojeska
Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
B. Recht, C. Re, S. Wright, F. Niu
How biased are maximum entropy models?
J. Macke, I. Murray, P. Latham
How Do Humans Teach: On Curriculum Learning and Teaching Dimension
F. Khan, X. Zhu, B. Mutlu
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning
Q. Le, A. Karpenko, J. Ngiam, A. Ng
Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis
S. Huang, J. Li, J. Ye, T. Wu, K. Chen, A. Fleisher, E. Reiman
Im2Text: Describing Images Using 1 Million Captioned Photographs
V. Ordonez, G. Kulkarni, T. Berg
Image Parsing with Stochastic Scene Grammar
Y. Zhao, S. Zhu
Improved Algorithms for Linear Stochastic Bandits
Y. Abbasi-yadkori, D. Pal, C. Szepesvari
Improving Topic Coherence with Regularized Topic Models
D. Newman, E. Bonilla, W. Buntine
Inductive reasoning about chimeric creatures
C. Kemp
Inference in continuous time changepoint point models
F. Stimberg, M. Opper, G. Sanguinetti, A. Ruttor
Inferring Interaction Networks using the IBP applied to microRNA Target Prediction
H. Le, Z. Bar-Joseph
Inferring spike-timing-dependent plasticity from spike train data
I. Stevenson, K. Koerding
Infinite Latent SVM for Classification and Multi-task Learning
J. Zhu, N. Chen, E. Xing
Information Rates and Optimal Decoding in Large Neural Populations
K. Rahnama Rad, L. Paninski
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions
M. Sorower, T. Dietterich, J. Doppa, W. Orr, P. Tadepalli, X. Fern
Iterative Learning for Reliable Crowdsourcing Systems
D. Karger, S. Oh, D. Shah
Joint 3D Estimation of Objects and Scene Layout
A. Geiger, C. Wojek, R. Urtasun
k-NN Regression Adapts to Local Intrinsic Dimension
S. Kpotufe
Kernel Bayes' Rule
K. Fukumizu, L. Song, A. Gretton
Kernel Embeddings of Latent Tree Graphical Models
L. Song, A. Parikh, E. Xing
Large-Scale Category Structure Aware Image Categorization
B. Zhao, F. Li, E. Xing
Large-Scale Sparse Principal Component Analysis with Application to Text Data
Y. Zhang, L. Ghaoui
Learning a Distance Metric from a Network
B. Shaw, B. Huang, T. Jebara
Learning Anchor Planes for Classification
Z. Zhang, L. Ladicky, P. Torr, A. Saffari
Learning a Tree of Metrics with Disjoint Visual Features
S. Hwang, K. Grauman, F. Sha
Learning Auto-regressive Models from Sequence and Non-sequence Data
T. Huang, J. Schneider
Learning Eigenvectors for Free
W. Koolen, W. Kotlowski, M. Warmuth
Learning Higher-Order Graph Structure with Features by Structure Penalty
S. Ding, G. Wahba, X. Zhu
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint
B. Sriperumbudur, K. Fukumizu, G. Lanckriet
Learning large-margin halfspaces with more malicious noise
P. Long, R. Servedio
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors
C. Yu, R. Greiner, H. Lin, V. Baracos
Learning person-object interactions for action recognition in still images
V. Delaitre, J. Sivic, I. Laptev
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities
A. Yao, J. Gall, L. Gool, R. Urtasun
Learning sparse inverse covariance matrices in the presence of confounders
O. Stegle, C. Lippert, J. Mooij, N. Lawrence, K. Borgwardt
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries
Z. Xiang, H. Xu, P. Ramadge
Learning to Agglomerate Superpixel Hierarchies
V. Jain, S. Turaga, K. Briggman, M. Helmstaedter, W. Denk, H. Seung
Learning to Learn with Compound HD Models
R. Salakhutdinov, J. Tenenbaum, A. Torralba
Learning to Search Efficiently in High Dimensions
Z. Li, H. Ning, L. Cao, T. Zhang, Y. Gong, T. Huang
Learning unbelievable marginal probabilities
X. Pitkow, Y. Ahmadian, K. Miller
Learning with the weighted trace-norm under arbitrary sampling distributions
R. Foygel, R. Salakhutdinov, O. Shamir, N. Srebro
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
Z. Lin, R. Liu, Z. Su
Linear Submodular Bandits and their Application to Diversified Retrieval
Y. Yue, C. Guestrin
Lower Bounds for Passive and Active Learning
M. Raginsky, A. Rakhlin
Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds
N. Shroff, P. Turaga, R. Chellappa
MAP Inference for Bayesian Inverse Reinforcement Learning
J. Choi, K. Kim
Matrix Completion for Image Classification
R. Cabral, F. De la Torre, J. Costeira, A. Bernardino
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning
X. Wang, X. Bai, X. Yang, W. Liu, L. Latecki
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
V. Mahadevan, C. Wong, J. Costa Pereira, T. Liu, N. Vasconcelos, L. Saul
Maximum Margin Multi-Label Structured Prediction
C. Lampert
Message-Passing for Approximate MAP Inference with Latent Variables
J. Jiang, P. Rai, H. Daume III
Metric Learning with Multiple Kernels
J. Wang, H. Do, A. Woznica, A. Kalousis
Minimax Localization of Structural Information in Large Noisy Matrices
M. Kolar, S. Balakrishnan, A. Rinaldo, A. Singh
Modelling Genetic Variations using Fragmentation-Coagulation Processes
Y. Teh, C. Blundell, L. Elliott
Monte Carlo Value Iteration with Macro-Actions
Z. Lim, D. Hsu, L. Sun
Multi-armed bandits on implicit metric spaces
A. Slivkins
Multi-Bandit Best Arm Identification
V. Gabillon, M. Ghavamzadeh, A. Lazaric, S. Bubeck
Multi-View Learning of Word Embeddings via CCA
P. Dhillon, D. Foster, L. Ungar
Multiclass Boosting: Theory and Algorithms
M. Saberian, N. Vasconcelos
Multiple Instance Filtering
K. Wnuk, S. Soatto
Multiple Instance Learning on Structured Data
D. Zhang, Y. Liu, L. Si, J. Zhang, R. Lawrence
Nearest Neighbor based Greedy Coordinate Descent
I. Dhillon, P. Ravikumar, A. Tewari
Neural Reconstruction with Approximate Message Passing (NeuRAMP)
A. Fletcher, S. Rangan, L. Varshney, A. Bhargava
Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability
D. Reichert, P. Series, A. Storkey
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction
E. Hazan, S. Kale
Noise Thresholds for Spectral Clustering
S. Balakrishnan, M. Xu, A. Krishnamurthy, A. Singh
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
F. Bach, E. Moulines
Non-conjugate Variational Message Passing for Multinomial and Binary Regression
D. Knowles, T. Minka
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels
V. Sindhwani, A. Lozano
Nonlinear Inverse Reinforcement Learning with Gaussian Processes
S. Levine, Z. Popovic, V. Koltun
Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation
O. Dikmen, C. Févotte
Nonstandard Interpretations of Probabilistic Programs for Efficient Inference
D. Wingate, N. Goodman, A. Stuhlmueller, J. Siskind
Object Detection with Grammar Models
R. Girshick, P. Felzenszwalb, D. Mcallester
On Learning Discrete Graphical Models using Greedy Methods
A. Jalali, C. Johnson, P. Ravikumar
Online Learning: Stochastic, Constrained, and Smoothed Adversaries
A. Rakhlin, K. Sridharan, A. Tewari
Online Submodular Set Cover, Ranking, and Repeated Active Learning
A. Guillory, J. Bilmes
On Strategy Stitching in Large Extensive Form Multiplayer Games
R. Gibson, D. Szafron
On the accuracy of l1-filtering of signals with block-sparse structure
A. Juditsky, F. Kilinc Karzan, A. Nemirovski, B. Polyak
On the Analysis of Multi-Channel Neural Spike Data
B. Chen, D. Carlson, L. Carin
On the Completeness of First-Order Knowledge Compilation for Lifted Probabilistic Inference
G. Van den Broeck
On the Universality of Online Mirror Descent
N. Srebro, K. Sridharan, A. Tewari
On Tracking The Partition Function
G. Desjardins, A. Courville, Y. Bengio
On U-processes and clustering performance
S. Clémençon
Optimal learning rates for least squares SVMs using Gaussian kernels
M. Eberts, I. Steinwart
Optimal Reinforcement Learning for Gaussian Systems
P. Hennig
Optimistic Optimization of Deterministic Functions
R. Munos
Orthogonal Matching Pursuit with Replacement
P. Jain, A. Tewari, I. Dhillon
PAC-Bayesian Analysis of Contextual Bandits
Y. Seldin, P. Auer, F. Laviolette, J. Shawe-Taylor, R. Ortner
Penalty Decomposition Methods for Rank Minimization
Y. Zhang, Z. Lu
Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning
J. Pajarinen, J. Peltonen
Phase transition in the family of p-resistances
M. Alamgir, U. von Luxburg
PiCoDes: Learning a Compact Code for Novel-Category Recognition
A. Bergamo, L. Torresani, A. Fitzgibbon
Policy Gradient Coagent Networks
P. Thomas
Portmanteau Vocabularies for Multi-Cue Image Representation
F. Khan, J. van de Weijer, A. Bagdanov, M. Vanrell
Practical Variational Inference for Neural Networks
A. Graves
Predicting Dynamic Difficulty
O. Missura, T. Gaertner
Predicting response time and error rates in visual search
B. Chen, V. Navalpakkam, P. Perona
Prediction strategies without loss
M. Kapralov, R. Panigrahy
Priors over Recurrent Continuous Time Processes
A. Saeedi, A. Bouchard-Côté
Prismatic Algorithm for Discrete D.C. Programming Problem
Y. Kawahara, T. Washio
Probabilistic amplitude and frequency demodulation
R. Turner, M. Sahani
Probabilistic Joint Image Segmentation and Labeling
A. Ion, J. Carreira, C. Sminchisescu
Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations
E. Orhan, R. Jacobs
Projection onto A Nonnegative Max-Heap
J. Liu, L. Sun, J. Ye
Pylon Model for Semantic Segmentation
V. Lempitsky, A. Vedaldi, A. Zisserman
Quasi-Newton Methods for Markov Chain Monte Carlo
Y. Zhang, C. Sutton
Query-Aware MCMC
M. Wick, A. McCallum
Randomized Algorithms for Comparison-based Search
D. Tschopp, S. Diggavi, P. Delgosha, S. Mohajer
Ranking annotators for crowdsourced labeling tasks
V. Raykar, S. Yu
Rapid Deformable Object Detection using Dual-Tree Branch-and-Bound
I. Kokkinos
Reconstructing Patterns of Information Diffusion from Incomplete Observations
F. Chierichetti, J. Kleinberg, D. Liben-Nowell
Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance
P. Gehler, C. Rother, M. Kiefel, L. Zhang, B. Schölkopf
Regularized Laplacian Estimation and Fast Eigenvector Approximation
P. Perry, M. Mahoney
Reinforcement Learning using Kernel-Based Stochastic Factorization
A. Barreto, D. Precup, J. Pineau
Relative Density-Ratio Estimation for Robust Distribution Comparison
M. Yamada, T. Suzuki, T. Kanamori, H. Hachiya, M. Sugiyama
Robust Lasso with missing and grossly corrupted observations
N. Nguyen, N. Nasrabadi, T. Tran
Robust Multi-Class Gaussian Process Classification
D. Hernández-lobato, J. Hernández-Lobato, P. Dupont
RTRMC: A Riemannian trust-region method for low-rank matrix completion
N. Boumal, P. Absil
Scalable Training of Mixture Models via Coresets
D. Feldman, M. Faulkner, A. Krause
See the Tree Through the Lines: The Shazoo Algorithm
F. Vitale, N. Cesa-Bianchi, C. Gentile, G. Zappella
Select and Sample: A Model of Efficient Neural Inference and Learning
J. Shelton, J. Bornschein, A. Sheikh, P. Berkes, J. Lucke
Selecting Receptive Fields in Deep Networks
A. Coates, A. Ng
Selecting the State-Representation in Reinforcement Learning
O. Maillard, R. Munos, D. Ryabko
Selective Prediction of Financial Trends with Hidden Markov Models
D. Pidan, R. El-Yaniv
Semantic Labeling of 3D Point Clouds for Indoor Scenes
H. Koppula, A. Anand, T. Joachims, A. Saxena
Semi-supervised Regression via Parallel Field Regularization
B. Lin, C. Zhang, X. He
Sequence learning with hidden units in spiking neural networks
J. Brea, W. Senn, J. Pfister
Shallow vs. Deep Sum-Product Networks
O. Delalleau, Y. Bengio
Shaping Level Sets with Submodular Functions
F. Bach
ShareBoost: Efficient multiclass learning with feature sharing
S. Shalev-Shwartz, Y. Wexler, A. Shashua
Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment
S. Kurtek, A. Srivastava, W. Wu
Similarity-based Learning via Data Driven Embeddings
P. Kar, P. Jain
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC
T. Pham, T. Chin, J. Yu, D. Suter
Solving Decision Problems with Limited Information
D. Maua, C. de Campos
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements
A. Waters, A. Sankaranarayanan, R. Baraniuk
Sparse Bayesian Multi-Task Learning
C. Archambeau, S. Guo, O. Zoeter
Sparse Estimation with Structured Dictionaries
D. Wipf
Sparse Features for PCA-Like Linear Regression
C. Boutsidis, P. Drineas, M. Magdon-Ismail
Sparse Filtering
J. Ngiam, P. Koh, Z. Chen, S. Bhaskar, A. Ng
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
C. Hsieh, M. Sustik, I. Dhillon, P. Ravikumar
Sparse Manifold Clustering and Embedding
E. Elhamifar, R. Vidal
Sparse recovery by thresholded non-negative least squares
M. Slawski, M. Hein
Sparse Recovery with Brownian Sensing
A. Carpentier, O. Maillard, R. Munos
Spatial distance dependent Chinese Restaurant Process for image segmentation
S. Ghosh, A. Ungureanu, E. Sudderth, D. Blei
Spectral Methods for Learning Multivariate Latent Tree Structure
A. Anandkumar, K. Chaudhuri, D. Hsu, S. Kakade, L. Song, T. Zhang
Speedy Q-Learning
M. Gheshlaghi Azar, R. Munos, M. Ghavamzadeh, H. Kappen
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning
M. Titsias, M. Lázaro-Gredilla
Statistical Performance of Convex Tensor Decomposition
R. Tomioka, T. Suzuki, K. Hayashi, H. Kashima
Statistical Tests for Optimization Efficiency
L. Boyles, A. Korattikara, D. Ramanan, M. Welling
Stochastic convex optimization with bandit feedback
A. Agarwal, D. Foster, D. Hsu, S. Kakade, A. Rakhlin
Structural equations and divisive normalization for energy-dependent component analysis
J. Hirayama, A. Hyvarinen
Structured Learning for Cell Tracking
X. Lou, F. Hamprecht
Structured sparse coding via lateral inhibition
a. szlam, K. Gregor, Y. LeCun
Structure Learning for Optimization
S. Yang, A. Rahimi
Submodular Multi-Label Learning
J. Petterson, T. Caetano
t-divergence Based Approximate Inference
N. Ding, S. Vishwanathan, Y. Qi
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification
I. Takeuchi, M. Sugiyama
TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning
G. Konidaris, S. Niekum, P. Thomas
Testing a Bayesian Measure of Representativeness Using a Large Image Database
J. Abbott, K. Heller, Z. Ghahramani, T. Griffiths
The Doubly Correlated Nonparametric Topic Model
D. Kim, E. Sudderth
The Fast Convergence of Boosting
M. Telgarsky
The Fixed Points of Off-Policy TD
J. Kolter
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers
L. Oneto, D. Anguita, A. Ghio, S. Ridella
The Kernel Beta Process
L. Ren, Y. Wang, D. Dunson, L. Carin
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning
M. Kloft, G. Blanchard
The Manifold Tangent Classifier
S. Rifai, Y. Dauphin, P. Vincent, Y. Bengio, X. Muller
Thinning Measurement Models and Questionnaire Design
R. Silva
Trace Lasso: a trace norm regularization for correlated designs
E. Grave, G. Obozinski, F. Bach
Transfer from Multiple MDPs
A. Lazaric, M. Restelli
Transfer Learning by Borrowing Examples
J. Lim, R. Salakhutdinov, A. Torralba
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories
C. Savin, P. Dayan, M. Lengyel
Understanding the Intrinsic Memorability of Images
P. Isola, D. Parikh, A. Torralba, A. Oliva
Unfolding Recursive Autoencoders for Paraphrase Detection
R. Socher, E. Huang, J. Pennin, A. Ng, C. Manning
Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning
T. Suzuki
Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction
S. Lyu
Uniqueness of Belief Propagation on Signed Graphs
Y. Watanabe
Universal low-rank matrix recovery from Pauli measurements
Y. Liu
Unsupervised learning models of primary cortical receptive fields and receptive field plasticity
A. Saxe, M. Bhand, R. Mudur, B. Suresh, A. Ng
Variance Penalizing AdaBoost
P. Shivaswamy, T. Jebara
Variance Reduction in Monte-Carlo Tree Search
J. Veness, M. Lanctot, M. Bowling
Variational Gaussian Process Dynamical Systems
A. Damianou, M. Titsias, N. Lawrence
Variational Learning for Recurrent Spiking Networks
D. Rezende, D. Wierstra, W. Gerstner
Video Annotation and Tracking with Active Learning
C. Vondrick, D. Ramanan
Why The Brain Separates Face Recognition From Object Recognition
J. Leibo, J. Mutch, T. Poggio