NeurIPS 2009

262 papers

Complexity of Decentralized Control: Special Cases

Martin Allen, Shlomo Zilberstein

Efficient Bregman Range Search

Lawrence Cayton

An Integer Projected Fixed Point Method for Graph Matching and MAP Inference

Marius Leordeanu, Martial Hebert, Rahul Sukthankar

Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition

Ashish Kapoor, Eric Horvitz

Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes

Kian M. Chai

Segmenting Scenes by Matching Image Composites

Bryan Russell, Alyosha Efros, Josef Sivic, Bill Freeman, Andrew Zisserman

Reading Tea Leaves: How Humans Interpret Topic Models

Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber, David M. Blei

Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise

Jacob Whitehill, Jacob Bergsma, Javier R. Movellan, Paul L. Ruvolo, Tingfan Wu

A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation

Lan Du, Lu Ren, Lawrence Carin, David B. Dunson

Nonparametric Bayesian Texture Learning and Synthesis

Long Zhu, Yuanahao Chen, Bill Freeman, Antonio Torralba

Measuring model complexity with the prior predictive

Wolf Vanpaemel

Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization

Massih R. Amini, Nicolas Usunier, Cyril Goutte

Beyond Convexity: Online Submodular Minimization

Elad Hazan, Satyen Kale

Human Rademacher Complexity

Xiaojin Zhu, Bryan R. Gibson, Timothy T. Rogers

Localizing Bugs in Program Executions with Graphical Models

Laura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer

Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction

Kwang I. Kim, Florian Steinke, Matthias Hein

Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models

Jonathan W Pillow, Jonathan W. Pillow

Boosting with Spatial Regularization

Yongxin Xi, Uri Hasson, Peter J. Ramadge, Zhen J. Xiang

Indian Buffet Processes with Power-law Behavior

Yee W. Teh, Dilan Gorur

Structural inference affects depth perception in the context of potential occlusion

Ian Stevenson, Konrad Koerding

A Bayesian Analysis of Dynamics in Free Recall

Richard Socher, Samuel Gershman, Per Sederberg, Kenneth Norman, Adler J. Perotte

Bayesian estimation of orientation preference maps

Sebastian Gerwinn, Leonard White, Matthias Kaschube, Matthias Bethge, Jakob H. Macke

Local Rules for Global MAP: When Do They Work ?

Kyomin Jung, Pushmeet Kohli, Devavrat Shah

Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units

Feng Yan, Ningyi Xu, Yuan Qi

Robust Value Function Approximation Using Bilinear Programming

Marek Petrik, Shlomo Zilberstein

Accelerated Gradient Methods for Stochastic Optimization and Online Learning

Chonghai Hu, Weike Pan, James T. Kwok

The Infinite Partially Observable Markov Decision Process

Finale Doshi-velez

Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning

Steven Chase, Andrew Schwartz, Wolfgang Maass, Robert A. Legenstein

An Online Algorithm for Large Scale Image Similarity Learning

Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio

Conditional Neural Fields

Jian Peng, Liefeng Bo, Jinbo Xu

Learning Non-Linear Combinations of Kernels

Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

Bayesian Source Localization with the Multivariate Laplace Prior

Marcel V. Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes

Multiple Incremental Decremental Learning of Support Vector Machines

Masayuki Karasuyama, Ichiro Takeuchi

Learning to Explore and Exploit in POMDPs

Chenghui Cai, Xuejun Liao, Lawrence Carin

A Rate Distortion Approach for Semi-Supervised Conditional Random Fields

Yang Wang, Gholamreza Haffari, Shaojun Wang, Greg Mori

Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs

Alexandre Bouchard-côté, Slav Petrov, Dan Klein

Know Thy Neighbour: A Normative Theory of Synaptic Depression

Jean-pascal Pfister, Peter Dayan, Máté Lengyel

An Additive Latent Feature Model for Transparent Object Recognition

Mario Fritz, Gary Bradski, Sergey Karayev, Trevor Darrell, Michael J. Black

Learning a Small Mixture of Trees

M. P. Kumar, Daphne Koller

Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference

Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum, Michael J. Black

Strategy Grafting in Extensive Games

Kevin Waugh, Nolan Bard, Michael Bowling

Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining

George Konidaris, Andrew G. Barto

Online Learning of Assignments

Matthew Streeter, Daniel Golovin, Andreas Krause

Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions

Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray

Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction

Grzegorz Swirszcz, Naoki Abe, Aurelie C. Lozano

A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers

Sahand Negahban, Bin Yu, Martin J. Wainwright, Pradeep K Ravikumar, Pradeep K. Ravikumar

Estimating image bases for visual image reconstruction from human brain activity

Yusuke Fujiwara, Yoichi Miyawaki, Yukiyasu Kamitani

On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation

Saketha N. Jagarlapudi, Dinesh G, Raman S, Chiranjib Bhattacharyya, Aharon Ben-tal

Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models

Ryan Mcdonald, Mehryar Mohri, Nathan Silberman, Dan Walker, Gideon S. Mann

Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models

Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han

Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model

Ed Vul, George Alvarez, Joshua B. Tenenbaum, Michael J. Black

A Smoothed Approximate Linear Program

Vijay Desai, Vivek Farias, Ciamac C. Moallemi

Distribution-Calibrated Hierarchical Classification

Ofer Dekel

Occlusive Components Analysis

Jörg Lücke, Richard Turner, Maneesh Sahani, Marc Henniges

Efficient and Accurate Lp-Norm Multiple Kernel Learning

Marius Kloft, Ulf Brefeld, Pavel Laskov, Klaus-Robert Müller, Alexander Zien

Discrete MDL Predicts in Total Variation

Marcus Hutter

Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations

Mingyuan Zhou, Haojun Chen, Lu Ren, Guillermo Sapiro, Lawrence Carin

Approximating MAP by Compensating for Structural Relaxations

Arthur Choi, Adnan Darwiche

Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition

Tom Ouyang, Randall Davis

A Biologically Plausible Model for Rapid Natural Scene Identification

Sennay Ghebreab, Steven Scholte, Victor Lamme, Arnold Smeulders

Variational Inference for the Nested Chinese Restaurant Process

Chong Wang, David M. Blei

Multi-Step Dyna Planning for Policy Evaluation and Control

Hengshuai Yao, Shalabh Bhatnagar, Dongcui Diao, Richard S. Sutton, Csaba Szepesvári

Unsupervised Feature Selection for the k-means Clustering Problem

Christos Boutsidis, Petros Drineas, Michael W. Mahoney

Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization

John Wright, Arvind Ganesh, Shankar Rao, Yigang Peng, Yi Ma

Nash Equilibria of Static Prediction Games

Michael Brückner, Tobias Scheffer

Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification

Wenming Zheng, Zhouchen Lin

Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions

Matthias Bethge, Eero P. Simoncelli, Fabian H. Sinz

A joint maximum-entropy model for binary neural population patterns and continuous signals

Sebastian Gerwinn, Philipp Berens, Matthias Bethge

Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing

Ruben Coen-cagli, Peter Dayan, Odelia Schwartz

Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing

Sundeep Rangan, Vivek Goyal, Alyson K. Fletcher

Speaker Comparison with Inner Product Discriminant Functions

Zahi Karam, Douglas Sturim, William M. Campbell

Statistical Consistency of Top-k Ranking

Fen Xia, Tie-yan Liu, Hang Li

Learning in Markov Random Fields using Tempered Transitions

Ruslan Salakhutdinov

Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation

Yusuke Watanabe, Kenji Fukumizu

Tracking Dynamic Sources of Malicious Activity at Internet Scale

Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck

Slow Learners are Fast

Martin Zinkevich, John Langford, Alex J. Smola

Learning to Rank by Optimizing NDCG Measure

Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao

The Ordered Residual Kernel for Robust Motion Subspace Clustering

Tat-jun Chin, Hanzi Wang, David Suter

Sufficient Conditions for Agnostic Active Learnable

Liwei Wang

Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness

Garvesh Raskutti, Bin Yu, Martin J. Wainwright

Maximum likelihood trajectories for continuous-time Markov chains

Theodore J. Perkins

Efficient Moments-based Permutation Tests

Chunxiao Zhou, Huixia J. Wang, Yongmei M. Wang

A Generalized Natural Actor-Critic Algorithm

Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya

Matrix Completion from Noisy Entries

Raghunandan Keshavan, Andrea Montanari, Sewoong Oh

Optimal Scoring for Unsupervised Learning

Zhihua Zhang, Guang Dai

Evaluating multi-class learning strategies in a generative hierarchical framework for object detection

Sanja Fidler, Marko Boben, Ales Leonardis

Fast Learning from Non-i.i.d. Observations

Ingo Steinwart, Andreas Christmann

Unsupervised Detection of Regions of Interest Using Iterative Link Analysis

Gunhee Kim, Antonio Torralba

Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions

Bangpeng Yao, Dirk Walther, Diane Beck, Li Fei-fei

Region-based Segmentation and Object Detection

Stephen Gould, Tianshi Gao, Daphne Koller

A General Projection Property for Distribution Families

Yuxi Li, Dale Schuurmans, Csaba Szepesvári, Yaoliang Yu, Yao-Liang Yu

Time-Varying Dynamic Bayesian Networks

Le Song, Mladen Kolar, Eric P. Xing

Regularized Distance Metric Learning:Theory and Algorithm

Rong Jin, Shijun Wang, Yang Zhou

Locality-sensitive binary codes from shift-invariant kernels

Maxim Raginsky, Svetlana Lazebnik

STDP enables spiking neurons to detect hidden causes of their inputs

Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass

Manifold Regularization for SIR with Rate Root-n Convergence

Wei Bian, Dacheng Tao

Ensemble Nystrom Method

Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability

Keith Bush, Joelle Pineau

Learning transport operators for image manifolds

Benjamin Culpepper, Bruno A. Olshausen

Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models

Baback Moghaddam, Mohammad Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin