NeurIPS 2010

292 papers

(RF)^2 -- Random Forest Random Field Nadia Payet, Sinisa Todorovic

A Bayesian Approach to Concept Drift Stephen Bach, Mark Maloof

A Bayesian Framework for Figure-Ground Interpretation Vicky Froyen, Jacob Feldman, Manish Singh

A Biologically Plausible Network for the Computation of Orientation Dominance Kritika Muralidharan, Nuno Vasconcelos

A Computational Decision Theory for Interactive Assistants Alan Fern, Prasad Tadepalli

A Dirty Model for Multi-Task Learning Ali Jalali, Sujay Sanghavi, Chao Ruan, Pradeep K. Ravikumar

A Discriminative Latent Model of Image Region and Object Tag Correspondence Yang Wang, Greg Mori

A Family of Penalty Functions for Structured Sparsity Jean Morales, Charles A. Micchelli, Massimiliano Pontil

A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration Yi-da Wu, Shi-jie Lin, Hsin Chen

A New Probabilistic Model for Rank Aggregation Tao Qin, Xiubo Geng, Tie-yan Liu

A Novel Family of Non-Parametric Cumulative Based Divergences for Point Processes Sohan Seth, Park Il, Austin Brockmeier, Mulugeta Semework, John Choi, Joseph Francis, Jose Principe

A Novel Kernel for Learning a Neuron Model from Spike Train Data Nicholas Fisher, Arunava Banerjee

A POMDP Extension with Belief-Dependent Rewards Mauricio Araya, Olivier Buffet, Vincent Thomas, Françcois Charpillet

A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups Sofia Mosci, Silvia Villa, Alessandro Verri, Lorenzo Rosasco

A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction Tamir Hazan, Raquel Urtasun

A Rational Decision Making Framework for Inhibitory Control Pradeep Shenoy, Angela J. Yu, Rajesh P. Rao

A Reduction from Apprenticeship Learning to Classification Umar Syed, Robert E. Schapire

A Theory of Multiclass Boosting Indraneel Mukherjee, Robert E. Schapire

A Unified Model of Short-Range and Long-Range Motion Perception Shuang Wu, Xuming He, Hongjing Lu, Alan L. Yuille

A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model Sebastian Millner, Andreas Grübl, Karlheinz Meier, Johannes Schemmel, Marc-olivier Schwartz

Accounting for Network Effects in Neuronal Responses Using L1 Regularized Point Process Models Ryan Kelly, Matthew Smith, Robert Kass, Tai S. Lee

Active Estimation of F-Measures Christoph Sawade, Niels Landwehr, Tobias Scheffer

Active Instance Sampling via Matrix Partition Yuhong Guo

Active Learning Applied to Patient-Adaptive Heartbeat Classification Jenna Wiens, John V. Guttag

Active Learning by Querying Informative and Representative Examples Sheng-jun Huang, Rong Jin, Zhi-Hua Zhou

Adaptive Multi-Task Lasso: With Application to eQTL Detection Seunghak Lee, Jun Zhu, Eric P. Xing

Agnostic Active Learning Without Constraints Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang

An Alternative to Low-Level-Sychrony-Based Methods for Speech Detection Javier R. Movellan, Paul L. Ruvolo

An Analysis on Negative Curvature Induced by Singularity in Multi-Layer Neural-Network Learning Eiji Mizutani, Stuart Dreyfus

An Approximate Inference Approach to Temporal Optimization in Optimal Control Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar

An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA Matthias Hein, Thomas Bühler

Approximate Inference by Compilation to Arithmetic Circuits Daniel Lowd, Pedro Domingos

Approximate Inference in Continuous Time Gaussian-Jump Processes Manfred Opper, Andreas Ruttor, Guido Sanguinetti

Attractor Dynamics with Synaptic Depression K. Wong, He Wang, Si Wu, Chi Fung

Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting Chris Barber, Joseph Bockhorst, Paul Roebber

Avoiding False Positive in Multi-Instance Learning Yanjun Han, Qing Tao, Jue Wang

B-Bit Minwise Hashing for Estimating Three-Way Similarities Ping Li, Arnd Konig, Wenhao Gui

Basis Construction from Power Series Expansions of Value Functions Sridhar Mahadevan, Bo Liu

Batch Bayesian Optimization via Simulation Matching Javad Azimi, Alan Fern, Xiaoli Z. Fern

Bayesian Action-Graph Games Albert X. Jiang, Kevin Leyton-brown

Beyond Actions: Discriminative Models for Contextual Group Activities Tian Lan, Yang Wang, Weilong Yang, Greg Mori

Block Variable Selection in Multivariate Regression and High-Dimensional Causal Inference Vikas Sindhwani, Aurelie C. Lozano

Boosting Classifier Cascades Nuno Vasconcelos, Mohammad J. Saberian

Bootstrapping Apprenticeship Learning Abdeslam Boularias, Brahim Chaib-draa

Brain Covariance Selection: Better Individual Functional Connectivity Models Using Population Prior Gael Varoquaux, Alexandre Gramfort, Jean-baptiste Poline, Bertrand Thirion

Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations Danial Lashkari, Ramesh Sridharan, Polina Golland

Causal Discovery in Multiple Models from Different Experiments Tom Claassen, Tom Heskes

Co-Regularization Based Semi-Supervised Domain Adaptation Abhishek Kumar, Avishek Saha, Hal Daume

Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm Nathan Srebro, Ruslan Salakhutdinov

Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning Matthias Broecheler, Lise Getoor

Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories George Konidaris, Scott Kuindersma, Roderic Grupen, Andrew G. Barto

Construction of Dependent Dirichlet Processes Based on Poisson Processes Dahua Lin, Eric Grimson, John W. Fisher

Convex Multiple-Instance Learning by Estimating Likelihood Ratio Fuxin Li, Cristian Sminchisescu

Copula Bayesian Networks Gal Elidan

Copula Processes Andrew G Wilson, Zoubin Ghahramani

Cross Species Expression Analysis Using a Dirichlet Process Mixture Model with Latent Matchings Ziv Bar-joseph, Hai-son P. Le

CUR from a Sparse Optimization Viewpoint Jacob Bien, Ya Xu, Michael W. Mahoney

Deciphering Subsampled Data: Adaptive Compressive Sampling as a Principle of Brain Communication Guy Isely, Christopher Hillar, Fritz Sommer

Decoding Ipsilateral Finger Movements from ECoG Signals in Humans Yuzong Liu, Mohit Sharma, Charles Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Eric Leuthardt, Kilian Q. Weinberger

Decomposing Isotonic Regression for Efficiently Solving Large Problems Ronny Luss, Saharon Rosset, Moni Shahar

Deep Coding Network Yuanqing Lin, Tong Zhang, Shenghuo Zhu, Kai Yu

Deterministic Single-Pass Algorithm for LDA Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa

Direct Loss Minimization for Structured Prediction Tamir Hazan, Joseph Keshet, David A. McAllester

Discriminative Clustering by Regularized Information Maximization Andreas Krause, Pietro Perona, Ryan G. Gomes

Distributed Dual Averaging in Networks Alekh Agarwal, Martin J. Wainwright, John C. Duchi

Distributionally Robust Markov Decision Processes Huan Xu, Shie Mannor

Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform Siwei Lyu

Double Q-Learning Hado V. Hasselt

Dynamic Infinite Relational Model for Time-Varying Relational Data Analysis Katsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda, Joshua B. Tenenbaum

Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks Kentaro Katahira, Kazuo Okanoya, Masato Okada

Efficient Algorithms for Learning Kernels from Multiple Similarity Matrices with General Convex Loss Functions Achintya Kundu, Vikram Tankasali, Chiranjib Bhattacharyya, Aharon Ben-tal

Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization Feiping Nie, Heng Huang, Xiao Cai, Chris H. Ding

Efficient Minimization of Decomposable Submodular Functions Peter Stobbe, Andreas Krause

Efficient Optimization for Discriminative Latent Class Models Armand Joulin, Jean Ponce, Francis R. Bach

Efficient Relational Learning with Hidden Variable Detection Ni Lao, Jun Zhu, Liu Liu, Yandong Liu, William W. Cohen

Empirical Bernstein Inequalities for U-Statistics Thomas Peel, Sandrine Anthoine, Liva Ralaivola

Empirical Risk Minimization with Approximations of Probabilistic Grammars Noah A. Smith, Shay B. Cohen

Energy Disaggregation via Discriminative Sparse Coding J. Z. Kolter, Siddharth Batra, Andrew Y. Ng

Epitome Driven 3-D Diffusion Tensor Image Segmentation: On Extracting Specific Structures Kamiya Motwani, Nagesh Adluru, Chris Hinrichs, Andrew Alexander, Vikas Singh

Error Propagation for Approximate Policy and Value Iteration Amir-massoud Farahmand, Csaba Szepesvári, Rémi Munos

Estimating Spatial Layout of Rooms Using Volumetric Reasoning About Objects and Surfaces Abhinav Gupta, Martial Hebert, Takeo Kanade, David M. Blei

Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs Dávid Pál, Barnabás Póczos, Csaba Szepesvári

Evaluating Neuronal Codes for Inference Using Fisher Information Haefner Ralf, Matthias Bethge

Evaluation of Rarity of Fingerprints in Forensics Chang Su, Sargur Srihari

Evidence-Specific Structures for Rich Tractable CRFs Anton Chechetka, Carlos Guestrin

Exact Inference and Learning for Cumulative Distribution Functions on Loopy Graphs Nebojsa Jojic, Chris Meek, Jim C. Huang

Exact Learning Curves for Gaussian Process Regression on Large Random Graphs Matthew Urry, Peter Sollich

Exploiting Weakly-Labeled Web Images to Improve Object Classification: A Domain Adaptation Approach Alessandro Bergamo, Lorenzo Torresani

Extended Bayesian Information Criteria for Gaussian Graphical Models Rina Foygel, Mathias Drton

Extensions of Generalized Binary Search to Group Identification and Exponential Costs Gowtham Bellala, Suresh Bhavnani, Clayton Scott

Factorized Latent Spaces with Structured Sparsity Yangqing Jia, Mathieu Salzmann, Trevor Darrell

Fast Detection of Multiple Change-Points Shared by Many Signals Using Group LARS Jean-philippe Vert, Kevin Bleakley

Fast Global Convergence Rates of Gradient Methods for High-Dimensional Statistical Recovery Alekh Agarwal, Sahand Negahban, Martin J. Wainwright

Fast Large-Scale Mixture Modeling with Component-Specific Data Partitions Bo Thiesson, Chong Wang

Feature Construction for Inverse Reinforcement Learning Sergey Levine, Zoran Popovic, Vladlen Koltun

Feature Set Embedding for Incomplete Data David Grangier, Iain Melvin

Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike Stella X. Yu

Fractionally Predictive Spiking Neurons Jaldert Rombouts, Sander M. Bohte

Functional Form of Motion Priors in Human Motion Perception Hongjing Lu, Tungyou Lin, Alan Lee, Luminita Vese, Alan L. Yuille

Functional Geometry Alignment and Localization of Brain Areas Georg Langs, Yanmei Tie, Laura Rigolo, Alexandra Golby, Polina Golland

Gated SoftMax Classification Roland Memisevic, Christopher Zach, Marc Pollefeys, Geoffrey E. Hinton

Gaussian Process Preference Elicitation Shengbo Guo, Scott Sanner, Edwin V. Bonilla

Gaussian Sampling by Local Perturbations George Papandreou, Alan L. Yuille

Generalized Roof Duality and Bisubmodular Functions Vladimir Kolmogorov

Generating More Realistic Images Using Gated MRF's Marc'aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton

Generative Local Metric Learning for Nearest Neighbor Classification Yung-kyun Noh, Byoung-tak Zhang, Daniel D. Lee

Getting Lost in Space: Large Sample Analysis of the Resistance Distance Ulrike V. Luxburg, Agnes Radl, Matthias Hein

Global Analytic Solution for Variational Bayesian Matrix Factorization Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka

Global Seismic Monitoring as Probabilistic Inference Nimar Arora, Stuart Russell, Paul Kidwell, Erik B. Sudderth

Graph-Valued Regression Han Liu, Xi Chen, Larry Wasserman, John D. Lafferty

Group Sparse Coding with a Laplacian Scale Mixture Prior Pierre Garrigues, Bruno A. Olshausen

Guaranteed Rank Minimization via Singular Value Projection Prateek Jain, Raghu Meka, Inderjit S. Dhillon

Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: A Deep Boltzmann Machine Model Peggy Series, David P. Reichert, Amos J. Storkey

Hashing Hyperplane Queries to near Points with Applications to Large-Scale Active Learning Prateek Jain, Sudheendra Vijayanarasimhan, Kristen Grauman

Heavy-Tailed Process Priors for Selective Shrinkage Fabian L. Wauthier, Michael I. Jordan

Humans Learn Using Manifolds, Reluctantly Tim Rogers, Chuck Kalish, Joseph Harrison, Xiaojin Zhu, Bryan R. Gibson

Identifying Dendritic Processing Aurel A. Lazar, Yevgeniy Slutskiy

Identifying Graph-Structured Activation Patterns in Networks James Sharpnack, Aarti Singh

Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch Zeeshan Syed, John V. Guttag

Implicit Differentiation by Perturbation Justin Domke

Implicit Encoding of Prior Probabilities in Optimal Neural Populations Deep Ganguli, Eero P. Simoncelli

Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation Mathieu Salzmann, Raquel Urtasun

Improvements to the Sequence Memoizer Jan Gasthaus, Yee W. Teh

Improving Human Judgments by Decontaminating Sequential Dependencies Michael Mozer, Harold Pashler, Matthew Wilder, Robert Lindsey, Matt Jones, Michael N. Jones

Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez

Individualized ROI Optimization via Maximization of Group-Wise Consistency of Structural and Functional Profiles Kaiming Li, Lei Guo, Carlos Faraco, Dajiang Zhu, Fan Deng, Tuo Zhang, Xi Jiang, Degang Zhang, Hanbo Chen, Xintao Hu, Steve Miller, Tianming Liu

Inductive Regularized Learning of Kernel Functions Prateek Jain, Brian Kulis, Inderjit S. Dhillon

Inference and Communication in the Game of Password Yang Xu, Charles Kemp

Inference with Multivariate Heavy-Tails in Linear Models Danny Bickson, Carlos Guestrin

Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics Kanaka Rajan, L Abbott, Haim Sompolinsky

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski, Hartwig Siebner, Lars K. Hansen

Inter-Time Segment Information Sharing for Non-Homogeneous Dynamic Bayesian Networks Dirk Husmeier, Frank Dondelinger, Sophie Lebre

Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains Martha White, Adam White

Joint Analysis of Time-Evolving Binary Matrices and Associated Documents Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin, David B. Dunson

Joint Cascade Optimization Using a Product of Boosted Classifiers Leonidas Lefakis, Francois Fleuret

Kernel Descriptors for Visual Recognition Liefeng Bo, Xiaofeng Ren, Dieter Fox

Label Embedding Trees for Large Multi-Class Tasks Samy Bengio, Jason Weston, David Grangier

Large Margin Learning of Upstream Scene Understanding Models Jun Zhu, Li-jia Li, Li Fei-fei, Eric P. Xing

Large Margin Multi-Task Metric Learning Shibin Parameswaran, Kilian Q. Weinberger

Large-Scale Matrix Factorization with Missing Data Under Additional Constraints Kaushik Mitra, Sameer Sheorey, Rama Chellappa

Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner, Lawrence K. Saul

Layer-Wise Analysis of Deep Networks with Gaussian Kernels Grégoire Montavon, Klaus-Robert Müller, Mikio L. Braun

Layered Image Motion with Explicit Occlusions, Temporal Consistency, and Depth Ordering Deqing Sun, Erik B. Sudderth, Michael J. Black

Learning Bounds for Importance Weighting Corinna Cortes, Yishay Mansour, Mehryar Mohri

Learning Concept Graphs from Text with Stick-Breaking Priors America Chambers, Padhraic Smyth, Mark Steyvers

Learning Convolutional Feature Hierarchies for Visual Recognition Koray Kavukcuoglu, Pierre Sermanet, Y-lan Boureau, Karol Gregor, Michael Mathieu, Yann L. Cun

Learning Efficient Markov Networks Vibhav Gogate, William Webb, Pedro Domingos

Learning from Candidate Labeling Sets Jie Luo, Francesco Orabona

Learning from Logged Implicit Exploration Data Alex Strehl, John Langford, Lihong Li, Sham M. Kakade

Learning Invariant Features Using the Transformed Indian Buffet Process Joseph L. Austerweil, Thomas L. Griffiths

Learning Kernels with Radiuses of Minimum Enclosing Balls Kun Gai, Guangyun Chen, Chang-shui Zhang

Learning Multiple Tasks Using Manifold Regularization Arvind Agarwal, Samuel Gerber, Hal Daume

Learning Multiple Tasks with a Sparse Matrix-Normal Penalty Yi Zhang, Jeff G. Schneider

Learning Networks of Stochastic Differential Equations José Pereira, Morteza Ibrahimi, Andrea Montanari

Learning Sparse Dynamic Linear Systems Using Stable Spline Kernels and Exponential Hyperpriors Alessandro Chiuso, Gianluigi Pillonetto

Learning the Context of a Category Dan Navarro

Learning to Combine Foveal Glimpses with a Third-Order Boltzmann Machine Hugo Larochelle, Geoffrey E. Hinton

Learning to Count Objects in Images Victor Lempitsky, Andrew Zisserman

Learning to Localise Sounds with Spiking Neural Networks Dan Goodman, Romain Brette

Learning via Gaussian Herding Koby Crammer, Daniel D. Lee

Lifted Inference Seen from the Other Side : The Tractable Features Abhay Jha, Vibhav Gogate, Alexandra Meliou, Dan Suciu

Linear Complementarity for Regularized Policy Evaluation and Improvement Jeffrey Johns, Christopher Painter-wakefield, Ronald Parr

Linear Readout from a Neural Population with Partial Correlation Data Adrien Wohrer, Ranulfo Romo, Christian K. Machens

Link Discovery Using Graph Feature Tracking Emile Richard, Nicolas Baskiotis, Theodoros Evgeniou, Nicolas Vayatis

Lower Bounds on Rate of Convergence of Cutting Plane Methods Xinhua Zhang, Ankan Saha, S.v.n. Vishwanathan

LSTD with Random Projections Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric Maillard, Rémi Munos

MAP Estimation for Graphical Models by Likelihood Maximization Akshat Kumar, Shlomo Zilberstein

MAP Estimation in Binary MRFs via Bipartite Multi-Cuts Sashank J. Reddi, Sunita Sarawagi, Sundar Vishwanathan

Minimum Average Cost Clustering Kiyohito Nagano, Yoshinobu Kawahara, Satoru Iwata

Mixture of Time-Warped Trajectory Models for Movement Decoding Elaine Corbett, Eric Perreault, Konrad Koerding

Monte-Carlo Planning in Large POMDPs David Silver, Joel Veness

More Data Means Less Inference: A Pseudo-Max Approach to Structured Learning David Sontag, Ofer Meshi, Amir Globerson, Tommi S. Jaakkola

Moreau-Yosida Regularization for Grouped Tree Structure Learning Jun Liu, Jieping Ye

Movement Extraction by Detecting Dynamics Switches and Repetitions Silvia Chiappa, Jan R. Peters

Multi-Label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition Serhat Bucak, Rong Jin, Anil K. Jain

Multi-Stage Dantzig Selector Ji Liu, Peter Wonka, Jieping Ye

Multi-View Active Learning in the Non-Realizable Case Wei Wang, Zhi-Hua Zhou

Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers Manas Pathak, Shantanu Rane, Bhiksha Raj

Multiple Kernel Learning and the SMO Algorithm Zhaonan Sun, Nawanol Ampornpunt, Manik Varma, S.v.n. Vishwanathan

Multitask Learning Without Label Correspondences Novi Quadrianto, James Petterson, Tibério S. Caetano, Alex J. Smola, S.v.n. Vishwanathan

Multivariate Dyadic Regression Trees for Sparse Learning Problems Han Liu, Xi Chen

Natural Policy Gradient Methods with Parameter-Based Exploration for Control Tasks Atsushi Miyamae, Yuichi Nagata, Isao Ono, Shigenobu Kobayashi

Near-Optimal Bayesian Active Learning with Noisy Observations Daniel Golovin, Andreas Krause, Debajyoti Ray

Network Flow Algorithms for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Francis R. Bach, Guillaume R. Obozinski

New Adaptive Algorithms for Online Classification Francesco Orabona, Koby Crammer

Non-Stochastic Bandit Slate Problems Satyen Kale, Lev Reyzin, Robert E. Schapire

Nonparametric Bayesian Policy Priors for Reinforcement Learning Finale Doshi-velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum

Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable Lauren Hannah, Warren Powell, David M. Blei

Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification Li-jia Li, Hao Su, Li Fei-fei, Eric P. Xing

Occlusion Detection and Motion Estimation with Convex Optimization Alper Ayvaci, Michalis Raptis, Stefano Soatto

On a Connection Between Importance Sampling and the Likelihood Ratio Policy Gradient Tang Jie, Pieter Abbeel

On Herding and the Perceptron Cycling Theorem Andrew Gelfand, Yutian Chen, Laurens Maaten, Max Welling

On the Convexity of Latent Social Network Inference Seth Myers, Jure Leskovec

On the Theory of Learnining with Privileged Information Dmitry Pechyony, Vladimir Vapnik

Online Classification with Specificity Constraints Andrey Bernstein, Shie Mannor, Nahum Shimkin

Online Learning for Latent Dirichlet Allocation Matthew Hoffman, Francis R. Bach, David M. Blei

Online Learning in the Manifold of Low-Rank Matrices Uri Shalit, Daphna Weinshall, Gal Chechik

Online Learning: Random Averages, Combinatorial Parameters, and Learnability Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Online Markov Decision Processes Under Bandit Feedback Gergely Neu, Andras Antos, András György, Csaba Szepesvári

Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets Paolo Viappiani, Craig Boutilier

Optimal Learning Rates for Kernel Conjugate Gradient Regression Gilles Blanchard, Nicole Krämer

Optimal Web-Scale Tiering as a Flow Problem Gilbert Leung, Novi Quadrianto, Kostas Tsioutsiouliklis, Alex J. Smola

Over-Complete Representations on Recurrent Neural Networks Can Support Persistent Percepts Shaul Druckmann, Dmitri B. Chklovskii

PAC-Bayesian Model Selection for Reinforcement Learning Mahdi M. Fard, Joelle Pineau

Parallelized Stochastic Gradient Descent Martin Zinkevich, Markus Weimer, Lihong Li, Alex J. Smola

Parametric Bandits: The Generalized Linear Case Sarah Filippi, Olivier Cappe, Aurélien Garivier, Csaba Szepesvári

Penalized Principal Component Regression on Graphs for Analysis of Subnetworks Ali Shojaie, George Michailidis

Permutation Complexity Bound on Out-Sample Error Malik Magdon-Ismail

Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine George Dahl, Marc'aurelio Ranzato, Abdel-rahman Mohamed, Geoffrey E. Hinton

Phoneme Recognition with Large Hierarchical Reservoirs Fabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen, Jean-pierre Martens

Policy Gradients in Linearly-Solvable MDPs Emanuel Todorov

Pose-Sensitive Embedding by Nonlinear NCA Regression Graham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler

Practical Large-Scale Optimization for Max-Norm Regularization Jason Lee, Ben Recht, Nathan Srebro, Joel Tropp, Ruslan Salakhutdinov

Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression Ling Huang, Jinzhu Jia, Bin Yu, Byung-gon Chun, Petros Maniatis, Mayur Naik

Predictive State Temporal Difference Learning Byron Boots, Geoffrey J. Gordon

Predictive Subspace Learning for Multi-View Data: A Large Margin Approach Ning Chen, Jun Zhu, Eric P. Xing

Probabilistic Belief Revision with Structural Constraints Peter Jones, Venkatesh Saligrama, Sanjoy Mitter

Probabilistic Deterministic Infinite Automata David Pfau, Nicholas Bartlett, Frank Wood

Probabilistic Inference and Differential Privacy Oliver Williams, Frank Mcsherry

Probabilistic Latent Variable Models for Distinguishing Between Cause and Effect Oliver Stegle, Dominik Janzing, Kun Zhang, Joris M. Mooij, Bernhard Schölkopf

Probabilistic Multi-Task Feature Selection Yu Zhang, Dit-Yan Yeung, Qian Xu

Random Conic Pursuit for Semidefinite Programming Ariel Kleiner, Ali Rahimi, Michael I. Jordan

Random Projection Trees Revisited Aman Dhesi, Purushottam Kar

Random Projections for $k$-Means Clustering Christos Boutsidis, Anastasios Zouzias, Petros Drineas

Random Walk Approach to Regret Minimization Hariharan Narayanan, Alexander Rakhlin

Rates of Convergence for the Cluster Tree Kamalika Chaudhuri, Sanjoy Dasgupta

Regularized Estimation of Image Statistics by Score Matching Diederik P. Kingma, Yann L. Cun

Relaxed Clipping: A Global Training Method for Robust Regression and Classification Min Yang, Linli Xu, Martha White, Dale Schuurmans, Yao-liang Yu

Repeated Games Against Budgeted Adversaries Jacob D. Abernethy, Manfred K. Warmuth

Rescaling, Thinning or Complementing? on Goodness-of-Fit Procedures for Point Process Models and Generalized Linear Models Felipe Gerhard, Wulfram Gerstner

Reverse Multi-Label Learning James Petterson, Tibério S. Caetano

Reward Design via Online Gradient Ascent Jonathan Sorg, Richard L. Lewis, Satinder P. Singh

Robust Clustering as Ensembles of Affinity Relations Hairong Liu, Longin J. Latecki, Shuicheng Yan

Robust PCA via Outlier Pursuit Huan Xu, Constantine Caramanis, Sujay Sanghavi

Sample Complexity of Testing the Manifold Hypothesis Hariharan Narayanan, Sanjoy Mitter

Scrambled Objects for Least-Squares Regression Odalric Maillard, Rémi Munos

Segmentation as Maximum-Weight Independent Set William Brendel, Sinisa Todorovic

Self-Paced Learning for Latent Variable Models M. P. Kumar, Benjamin Packer, Daphne Koller

Semi-Supervised Learning with Adversarially Missing Label Information Umar Syed, Ben Taskar

Shadow Dirichlet for Restricted Probability Modeling Bela Frigyik, Maya Gupta, Yihua Chen

Short-Term Memory in Neuronal Networks Through Dynamical Compressed Sensing Surya Ganguli, Haim Sompolinsky

Sidestepping Intractable Inference with Structured Ensemble Cascades David Weiss, Benjamin Sapp, Ben Taskar

Simultaneous Object Detection and Ranking with Weak Supervision Matthew Blaschko, Andrea Vedaldi, Andrew Zisserman

Size Matters: Metric Visual Search Constraints from Monocular Metadata Mario Fritz, Kate Saenko, Trevor Darrell

Slice Sampling Covariance Hyperparameters of Latent Gaussian Models Iain Murray, Ryan P. Adams

Smoothness, Low Noise and Fast Rates Nathan Srebro, Karthik Sridharan, Ambuj Tewari

Sodium Entry Efficiency During Action Potentials: A Novel Single-Parameter Family of Hodgkin-Huxley Models Anand Singh, Renaud Jolivet, Pierre Magistretti, Bruno Weber

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake Stefan Harmeling, Hirsch Michael, Bernhard Schölkopf

Sparse Coding for Learning Interpretable Spatio-Temporal Primitives Taehwan Kim, Gregory Shakhnarovich, Raquel Urtasun

Sparse Instrumental Variables (SPIV) for Genome-Wide Studies Paul Mckeigue, Jon Krohn, Amos J. Storkey, Felix V. Agakov

Sparse Inverse Covariance Selection via Alternating Linearization Methods Katya Scheinberg, Shiqian Ma, Donald Goldfarb

Spatial and Anatomical Regularization of SVM for Brain Image Analysis Remi Cuingnet, Marie Chupin, Habib Benali, Olivier Colliot

Spectral Regularization for Support Estimation Ernesto D. Vito, Lorenzo Rosasco, Alessandro Toigo

Sphere Embedding: An Application to Part-of-Speech Induction Yariv Maron, Michael Lamar, Elie Bienenstock

Spike Timing-Dependent Plasticity as Dynamic Filter Joscha Schmiedt, Christian Albers, Klaus Pawelzik

SpikeAnts, a Spiking Neuron Network Modelling the Emergence of Organization in a Complex System Sylvain Chevallier, Hél\`ene Paugam-moisy, Michele Sebag

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Han Liu, Kathryn Roeder, Larry Wasserman

Static Analysis of Binary Executables Using Structural SVMs Nikos Karampatziakis

Structural Epitome: A Way to Summarize One’s Visual Experience Nebojsa Jojic, Alessandro Perina, Vittorio Murino

Structured Determinantal Point Processes Alex Kulesza, Ben Taskar

Structured Sparsity-Inducing Norms Through Submodular Functions Francis R. Bach

Subgraph Detection Using Eigenvector L1 Norms Benjamin Miller, Nadya Bliss, Patrick J. Wolfe

Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework Hongbo Zhou, Qiang Cheng

Supervised Clustering Pranjal Awasthi, Reza B. Zadeh

Switched Latent Force Models for Movement Segmentation Mauricio Alvarez, Jan R. Peters, Neil D. Lawrence, Bernhard Schölkopf

Switching State Space Model for Simultaneously Estimating State Transitions and Nonstationary Firing Rates Ken Takiyama, Masato Okada

Synergies in Learning Words and Their Referents Mark Johnson, Katherine Demuth, Bevan Jones, Michael J. Black

T-Logistic Regression Nan Ding, S.v.n. Vishwanathan

The LASSO Risk: Asymptotic Results and Real World Examples Mohsen Bayati, José Pereira, Andrea Montanari

The Maximal Causes of Natural Scenes Are Edge Filters Jose Puertas, Joerg Bornschein, Jörg Lücke

The Multidimensional Wisdom of Crowds Peter Welinder, Steve Branson, Pietro Perona, Serge J. Belongie

The Neural Costs of Optimal Control Samuel Gershman, Robert Wilson

Throttling Poisson Processes Uwe Dick, Peter Haider, Thomas Vanck, Michael Brückner, Tobias Scheffer

Tight Sample Complexity of Large-Margin Learning Sivan Sabato, Nathan Srebro, Naftali Tishby

Tiled Convolutional Neural Networks Jiquan Ngiam, Zhenghao Chen, Daniel Chia, Pang W. Koh, Quoc V. Le, Andrew Y. Ng

Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models Congcong Li, Adarsh Kowdle, Ashutosh Saxena, Tsuhan Chen

Towards Property-Based Classification of Clustering Paradigms Margareta Ackerman, Shai Ben-David, David Loker

Trading Off Mistakes and Don't-Know Predictions Amin Sayedi, Morteza Zadimoghaddam, Avrim Blum

Transduction with Matrix Completion: Three Birds with One Stone Andrew Goldberg, Ben Recht, Junming Xu, Robert Nowak, Xiaojin Zhu

Tree-Structured Stick Breaking for Hierarchical Data Zoubin Ghahramani, Michael I. Jordan, Ryan P. Adams

Two-Layer Generalization Analysis for Ranking Using Rademacher Average Wei Chen, Tie-yan Liu, Zhi-ming Ma

Universal Consistency of Multi-Class Support Vector Classification Tobias Glasmachers

Universal Kernels on Non-Standard Input Spaces Andreas Christmann, Ingo Steinwart

Unsupervised Kernel Dimension Reduction Meihong Wang, Fei Sha, Michael I. Jordan

Using Body-Anchored Priors for Identifying Actions in Single Images Leonid Karlinsky, Michael Dinerstein, Shimon Ullman

Variable Margin Losses for Classifier Design Hamed Masnadi-shirazi, Nuno Vasconcelos

Variational Bounds for Mixed-Data Factor Analysis Mohammad Emtiyaz Khan, Guillaume Bouchard, Kevin P. Murphy, Benjamin M. Marlin

Variational Inference over Combinatorial Spaces Alexandre Bouchard-côté, Michael I. Jordan

Why Are Some Word Orders More Common than Others? a Uniform Information Density Account Luke Maurits, Dan Navarro, Amy Perfors

Word Features for Latent Dirichlet Allocation James Petterson, Wray Buntine, Shravan M. Narayanamurthy, Tibério S. Caetano, Alex J. Smola

Worst-Case Bounds on the Quality of Max-Product Fixed-Points Meritxell Vinyals, Jes\'us Cerquides, Alessandro Farinelli, Juan A. Rodríguez-aguilar

Worst-Case Linear Discriminant Analysis Yu Zhang, Dit-Yan Yeung