Book

Monte Carlo Sampling for Regret Minimization in Extensive Games Marc Lanctot, Kevin Waugh, Martin Zinkevich, Michael Bowling

DUOL: A Double Updating Approach for Online Learning Peilin Zhao, Steven Hoi, Rong Jin

Compressed Least-Squares Regression Odalric Maillard, Rémi Munos

White Functionals for Anomaly Detection in Dynamical Systems Marco Cuturi, Jean-philippe Vert, Alexandre D'aspremont

Learning models of object structure Joseph Schlecht, Kobus Barnard

Neurometric function analysis of population codes Philipp Berens, Sebastian Gerwinn, Alexander Ecker, Matthias Bethge

Slow, Decorrelated Features for Pretraining Complex Cell-like Networks Yoshua Bengio, James Bergstra

Code-specific policy gradient rules for spiking neurons Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner

Positive Semidefinite Metric Learning with Boosting Chunhua Shen, Junae Kim, Lei Wang, Anton Hengel

Spatial Normalized Gamma Processes Vinayak Rao, Yee Teh

Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification Amarnag Subramanya, Jeff A. Bilmes

Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks Stefan Klampfl, Wolfgang Maass

Free energy score space Alessandro Perina, Marco Cristani, Umberto Castellani, Vittorio Murino, Nebojsa Jojic

Multi-Label Prediction via Sparse Infinite CCA Piyush Rai, Hal Daume

Fast subtree kernels on graphs Nino Shervashidze, Karsten Borgwardt

Directed Regression Yi-hao Kao, Benjamin Roy, Xiang Yan

Nonparametric Greedy Algorithms for the Sparse Learning Problem Han Liu, Xi Chen

Rethinking LDA: Why Priors Matter Hanna Wallach, David Mimno, Andrew McCallum

Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity Andreas Bartels, Matthew Blaschko, Jacquelyn Shelton

Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning Anne Hsu, Thomas Griffiths

Non-stationary continuous dynamic Bayesian networks Marco Grzegorczyk, Dirk Husmeier

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye

Potential-Based Agnostic Boosting Varun Kanade, Adam Kalai

Gaussian process regression with Student-t likelihood Jarno Vanhatalo, Pasi Jylänki, Aki Vehtari

Bilinear classifiers for visual recognition Hamed Pirsiavash, Deva Ramanan, Charless Fowlkes

Zero-shot Learning with Semantic Output Codes Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell

Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition Natasha Singh-miller, Michael Collins

Semi-Supervised Learning in Gigantic Image Collections Rob Fergus, Yair Weiss, Antonio Torralba

Sensitivity analysis in HMMs with application to likelihood maximization Pierre-arnaud Coquelin, Romain Deguest, Rémi Munos

Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation Jie Luo, Barbara Caputo, Vittorio Ferrari

Streaming Pointwise Mutual Information Benjamin Durme, Ashwin Lall

Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution Cosmin Bejan, Matthew Titsworth, Andrew Hickl, Sanda Harabagiu

A Stochastic approximation method for inference in probabilistic graphical models Peter Carbonetto, Matthew King, Firas Hamze

Factor Modeling for Advertisement Targeting Ye Chen, Michael Kapralov, John Canny, Dmitry Pavlov

Sparse Estimation Using General Likelihoods and Non-Factorial Priors David Wipf, Srikantan Nagarajan

Modeling the spacing effect in sequential category learning Hongjing Lu, Matthew Weiden, Alan L. Yuille

An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism Douglas Eck, Yoshua Bengio, Aaron C. Courville

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process Finale Doshi-velez, Shakir Mohamed, Zoubin Ghahramani, David Knowles

Matrix Completion from Power-Law Distributed Samples Raghu Meka, Prateek Jain, Inderjit Dhillon

Filtering Abstract Senses From Image Search Results Kate Saenko, Trevor Darrell

Heavy-Tailed Symmetric Stochastic Neighbor Embedding Zhirong Yang, Irwin King, Zenglin Xu, Erkki Oja

Which graphical models are difficult to learn? Andrea Montanari, Jose Pereira

Information-theoretic lower bounds on the oracle complexity of convex optimization Alekh Agarwal, Martin J. Wainwright, Peter Bartlett, Pradeep Ravikumar

Linear-time Algorithms for Pairwise Statistical Problems Parikshit Ram, Dongryeol Lee, William March, Alexander Gray

From PAC-Bayes Bounds to KL Regularization Pascal Germain, Alexandre Lacasse, Mario Marchand, Sara Shanian, François Laviolette

On Stochastic and Worst-case Models for Investing Elad Hazan, Satyen Kale

Structured output regression for detection with partial truncation Andrea Vedaldi, Andrew Zisserman

On Invariance in Hierarchical Models Jake Bouvrie, Lorenzo Rosasco, Tomaso Poggio

Submanifold density estimation Arkadas Ozakin, Alexander Gray

Nonlinear Learning using Local Coordinate Coding Kai Yu, Tong Zhang, Yihong Gong

No evidence for active sparsification in the visual cortex Pietro Berkes, Ben White, Jozsef Fiser

Distribution Matching for Transduction Novi Quadrianto, James Petterson, Alex Smola

Canonical Time Warping for Alignment of Human Behavior Feng Zhou, Fernando Torre

A Parameter-free Hedging Algorithm Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu

Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering Lei Wu, Rong Jin, Steven Hoi, Jianke Zhu, Nenghai Yu

Ranking Measures and Loss Functions in Learning to Rank Wei Chen, Tie-yan Liu, Yanyan Lan, Zhi-ming Ma, Hang Li

Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection Roy Anati, Kostas Daniilidis

Replicated Softmax: an Undirected Topic Model Geoffrey E. Hinton, Russ R. Salakhutdinov

Fast, smooth and adaptive regression in metric spaces Samory Kpotufe

Bayesian Belief Polarization Alan Jern, Kai-min Chang, Charles Kemp

Linearly constrained Bayesian matrix factorization for blind source separation Mikkel Schmidt

Sparse and Locally Constant Gaussian Graphical Models Jean Honorio, Dimitris Samaras, Nikos Paragios, Rita Goldstein, Luis E. Ortiz

Sparse Metric Learning via Smooth Optimization Yiming Ying, Kaizhu Huang, Colin Campbell

The 'tree-dependent components' of natural scenes are edge filters Daniel Zoran, Yair Weiss

Bootstrapping from Game Tree Search Joel Veness, David Silver, Alan Blair, William Uther

Individuation, Identification and Object Discovery Charles Kemp, Alan Jern, Fei Xu

Modeling Social Annotation Data with Content Relevance using a Topic Model Tomoharu Iwata, Takeshi Yamada, Naonori Ueda

Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton, Hamid Maei, Csaba Szepesvári

Group Sparse Coding Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow

Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process Chong Wang, David Blei

Fast Image Deconvolution using Hyper-Laplacian Priors Dilip Krishnan, Rob Fergus

Compositionality of optimal control laws Emanuel Todorov

AUC optimization and the two-sample problem Nicolas Vayatis, Marine Depecker, Stéphan Clémençcon

Measuring Invariances in Deep Networks Ian Goodfellow, Honglak Lee, Quoc Le, Andrew Saxe, Andrew Ng

Nonparametric Latent Feature Models for Link Prediction Kurt Miller, Michael Jordan, Thomas Griffiths

Asymptotically Optimal Regularization in Smooth Parametric Models Percy S. Liang, Guillaume Bouchard, Francis Bach, Michael Jordan

Variational Gaussian-process factor analysis for modeling spatio-temporal data Jaakko Luttinen, Alexander Ilin

Lattice Regression Eric Garcia, Maya Gupta

Sharing Features among Dynamical Systems with Beta Processes Emily Fox, Michael Jordan, Erik Sudderth, Alan Willsky

The Wisdom of Crowds in the Recollection of Order Information Mark Steyvers, Brent Miller, Pernille Hemmer, Michael Lee

Efficient Recovery of Jointly Sparse Vectors Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye

Efficient Match Kernel between Sets of Features for Visual Recognition Liefeng Bo, Cristian Sminchisescu

Clustering sequence sets for motif discovery Jong Kim, Seungjin Choi

Bayesian Nonparametric Models on Decomposable Graphs Francois Caron, Arnaud Doucet

Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies Arno Onken, Steffen Grünewälder, Klaus Obermayer

Streaming k-means approximation Nir Ailon, Ragesh Jaiswal, Claire Monteleoni

Help or Hinder: Bayesian Models of Social Goal Inference Tomer Ullman, Chris Baker, Owen Macindoe, Owain Evans, Noah Goodman, Joshua Tenenbaum

Sequential effects reflect parallel learning of multiple environmental regularities Matthew Wilder, Matt Jones, Michael C. Mozer

Noisy Generalized Binary Search Robert Nowak

Solving Stochastic Games Liam Dermed, Charles Isbell

Modelling Relational Data using Bayesian Clustered Tensor Factorization Ilya Sutskever, Joshua Tenenbaum, Russ R. Salakhutdinov

Kernel Methods for Deep Learning Youngmin Cho, Lawrence Saul

Optimal context separation of spiking haptic signals by second-order somatosensory neurons Romain Brasselet, Roland Johansson, Angelo Arleo

Heterogeneous multitask learning with joint sparsity constraints Xiaolin Yang, Seyoung Kim, Eric Xing

Learning with Compressible Priors Volkan Cevher

Inter-domain Gaussian Processes for Sparse Inference using Inducing Features Miguel Lázaro-Gredilla, Aníbal Figueiras-Vidal

Particle-based Variational Inference for Continuous Systems Andrew Frank, Padhraic Smyth, Alexander Ihler

Efficient Learning using Forward-Backward Splitting Yoram Singer, John C. Duchi

$L_1$-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry Arnak Dalalyan, Renaud Keriven

Learning to Hash with Binary Reconstructive Embeddings Brian Kulis, Trevor Darrell

Multi-Label Prediction via Compressed Sensing Daniel J. Hsu, Sham M. Kakade, John Langford, Tong Zhang

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions Kenji Fukumizu, Arthur Gretton, Gert Lanckriet, Bernhard Schölkopf, Bharath K. Sriperumbudur

Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data Boaz Nadler, Nathan Srebro, Xueyuan Zhou

Maximin affinity learning of image segmentation Kevin Briggman, Winfried Denk, Sebastian Seung, Moritz Helmstaedter, Srinivas C. Turaga

Perceptual Multistability as Markov Chain Monte Carlo Inference Samuel Gershman, Ed Vul, Joshua Tenenbaum

Probabilistic Relational PCA Wu-jun Li, Dit-Yan Yeung, Zhihua Zhang

Adapting to the Shifting Intent of Search Queries Umar Syed, Aleksandrs Slivkins, Nina Mishra

Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory Harold Pashler, Nicholas Cepeda, Robert V. Lindsey, Ed Vul, Michael C. Mozer

A Game-Theoretic Approach to Hypergraph Clustering Samuel Bulò, Marcello Pelillo

Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora Shuang-hong Yang, Hongyuan Zha, Bao-gang Hu

Adaptive Design Optimization in Experiments with People Daniel Cavagnaro, Jay Myung, Mark Pitt

Riffled Independence for Ranked Data Jonathan Huang, Carlos Guestrin

A Neural Implementation of the Kalman Filter Robert Wilson, Leif Finkel

An LP View of the M-best MAP problem Menachem Fromer, Amir Globerson

Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing Matthias Seeger

Toward Provably Correct Feature Selection in Arbitrary Domains Dimitris Margaritis

3D Object Recognition with Deep Belief Nets Vinod Nair, Geoffrey E. Hinton

Improving Existing Fault Recovery Policies Guy Shani, Christopher Meek

Convex Relaxation of Mixture Regression with Efficient Algorithms Novi Quadrianto, John Lim, Dale Schuurmans, Tibério Caetano

Hierarchical Learning of Dimensional Biases in Human Categorization Adam Sanborn, Nick Chater, Katherine A. Heller

Polynomial Semantic Indexing Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri

Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling Lei Shi, Thomas Griffiths

Discriminative Network Models of Schizophrenia Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-laure Paillere-martinot, Catherine Martelli, Jean-luc Martinot, Jean-baptiste Poline, Guillermo Cecchi

Sparsistent Learning of Varying-coefficient Models with Structural Changes Mladen Kolar, Le Song, Eric Xing

Dual Averaging Method for Regularized Stochastic Learning and Online Optimization Lin Xiao

Analysis of SVM with Indefinite Kernels Yiming Ying, Colin Campbell, Mark Girolami

Quantification and the language of thought Charles Kemp

Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis Barry Chai, Dirk Walther, Diane Beck, Li Fei-fei

Semi-supervised Learning using Sparse Eigenfunction Bases Kaushik Sinha, Mikhail Belkin

On Learning Rotations Raman Arora

A Gaussian Tree Approximation for Integer Least-Squares Jacob Goldberger, Amir Leshem

Nonlinear directed acyclic structure learning with weakly additive noise models Arthur Gretton, Peter Spirtes, Robert Tillman

FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs Andrew McCallum, Karl Schultz, Sameer Singh

Exponential Family Graph Matching and Ranking James Petterson, Jin Yu, Julian Mcauley, Tibério Caetano

Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out Yicong Meng, Bertram Shi

Periodic Step Size Adaptation for Single Pass On-line Learning Chun-nan Hsu, Yu-ming Chang, Hanshen Huang, Yuh-jye Lee

Construction of Nonparametric Bayesian Models from Parametric Bayes Equations Peter Orbanz

Adaptive Regularization for Transductive Support Vector Machine Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu, Zhirong Yang

Subject independent EEG-based BCI decoding Siamac Fazli, Cristian Grozea, Marton Danoczy, Benjamin Blankertz, Florin Popescu, Klaus-Robert Müller

On the Convergence of the Concave-Convex Procedure Gert Lanckriet, Bharath K. Sriperumbudur

Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis Sundeep Rangan, Alyson K. Fletcher

Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording Zhi Yang, Qi Zhao, Edward Keefer, Wentai Liu

Adaptive Regularization of Weight Vectors Koby Crammer, Alex Kulesza, Mark Dredze

Posterior vs Parameter Sparsity in Latent Variable Models Kuzman Ganchev, Ben Taskar, Fernando Pereira, João Gama

Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) Tao Hu, Anthony Leonardo, Dmitri Chklovskii

Label Selection on Graphs Andrew Guillory, Jeff A. Bilmes

A Fast, Consistent Kernel Two-Sample Test Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur

Robust Nonparametric Regression with Metric-Space Valued Output Matthias Hein

Kernels and learning curves for Gaussian process regression on random graphs Peter Sollich, Matthew Urry, Camille Coti

Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation Shuheng Zhou

Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships Tomasz Malisiewicz, Alyosha Efros

Conditional Random Fields with High-Order Features for Sequence Labeling Nan Ye, Wee Lee, Hai Chieu, Dan Wu

Abstraction and Relational learning Charles Kemp, Alan Jern

Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming Xiao-ming Wu, Anthony So, Zhenguo Li, Shuo-yen Li

A Data-Driven Approach to Modeling Choice Vivek Farias, Srikanth Jagabathula, Devavrat Shah

Anomaly Detection with Score functions based on Nearest Neighbor Graphs Manqi Zhao, Venkatesh Saligrama

Submodularity Cuts and Applications Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes

Bayesian Sparse Factor Models and DAGs Inference and Comparison Ricardo Henao, Ole Winther

A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds Paris Smaragdis, Madhusudana Shashanka, Bhiksha Raj

Data-driven calibration of linear estimators with minimal penalties Sylvain Arlot, Francis Bach

fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity Bryan Conroy, Ben Singer, James Haxby, Peter J. Ramadge

Unsupervised feature learning for audio classification using convolutional deep belief networks Honglak Lee, Peter Pham, Yan Largman, Andrew Ng

Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models Baback Moghaddam, Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin

Learning transport operators for image manifolds Benjamin Culpepper, Bruno Olshausen

Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability Keith Bush, Joelle Pineau

Ensemble Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

Manifold Regularization for SIR with Rate Root-n Convergence Wei Bian, Dacheng Tao

STDP enables spiking neurons to detect hidden causes of their inputs Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass

Locality-sensitive binary codes from shift-invariant kernels Maxim Raginsky, Svetlana Lazebnik

Regularized Distance Metric Learning:Theory and Algorithm Rong Jin, Shijun Wang, Yang Zhou

Time-Varying Dynamic Bayesian Networks Le Song, Mladen Kolar, Eric Xing

A General Projection Property for Distribution Families Yao-liang Yu, Yuxi Li, Dale Schuurmans, Csaba Szepesvári

Region-based Segmentation and Object Detection Stephen Gould, Tianshi Gao, Daphne Koller

Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions Bangpeng Yao, Dirk Walther, Diane Beck, Li Fei-fei

Unsupervised Detection of Regions of Interest Using Iterative Link Analysis Gunhee Kim, Antonio Torralba

Fast Learning from Non-i.i.d. Observations Ingo Steinwart, Andreas Christmann

Evaluating multi-class learning strategies in a generative hierarchical framework for object detection Sanja Fidler, Marko Boben, Ales Leonardis

Optimal Scoring for Unsupervised Learning Zhihua Zhang, Guang Dai

Matrix Completion from Noisy Entries Raghunandan Keshavan, Andrea Montanari, Sewoong Oh

A Generalized Natural Actor-Critic Algorithm Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya

Efficient Moments-based Permutation Tests Chunxiao Zhou, Huixia Wang, Yongmei Wang

Maximum likelihood trajectories for continuous-time Markov chains Theodore Perkins

Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness Garvesh Raskutti, Bin Yu, Martin J. Wainwright

Sufficient Conditions for Agnostic Active Learnable Liwei Wang

The Ordered Residual Kernel for Robust Motion Subspace Clustering Tat-jun Chin, Hanzi Wang, David Suter

Learning to Rank by Optimizing NDCG Measure Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao

Slow Learners are Fast Martin Zinkevich, John Langford, Alex Smola

Tracking Dynamic Sources of Malicious Activity at Internet Scale Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck

Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation Yusuke Watanabe, Kenji Fukumizu

Learning in Markov Random Fields using Tempered Transitions Russ R. Salakhutdinov

Statistical Consistency of Top-k Ranking Fen Xia, Tie-yan Liu, Hang Li

Speaker Comparison with Inner Product Discriminant Functions Zahi Karam, Douglas Sturim, William Campbell

Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing Sundeep Rangan, Vivek Goyal, Alyson K. Fletcher

Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing Ruben Coen-cagli, Peter Dayan, Odelia Schwartz

A joint maximum-entropy model for binary neural population patterns and continuous signals Sebastian Gerwinn, Philipp Berens, Matthias Bethge

Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions Matthias Bethge, Eero Simoncelli, Fabian Sinz

Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification Wenming Zheng, Zhouchen Lin

Nash Equilibria of Static Prediction Games Michael Brückner, Tobias Scheffer

Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization John Wright, Arvind Ganesh, Shankar Rao, Yigang Peng, Yi Ma

Unsupervised Feature Selection for the $k$-means Clustering Problem Christos Boutsidis, Petros Drineas, Michael W. Mahoney

Multi-Step Dyna Planning for Policy Evaluation and Control Hengshuai Yao, Shalabh Bhatnagar, Dongcui Diao, Richard S. Sutton, Csaba Szepesvári

Variational Inference for the Nested Chinese Restaurant Process Chong Wang, David Blei

A Biologically Plausible Model for Rapid Natural Scene Identification Sennay Ghebreab, Steven Scholte, Victor Lamme, Arnold Smeulders

Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition Tom Ouyang, Randall Davis

Approximating MAP by Compensating for Structural Relaxations Arthur Choi, Adnan Darwiche

Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations Mingyuan Zhou, Haojun Chen, Lu Ren, Guillermo Sapiro, Lawrence Carin, John Paisley

Discrete MDL Predicts in Total Variation Marcus Hutter

Efficient and Accurate Lp-Norm Multiple Kernel Learning Marius Kloft, Ulf Brefeld, Pavel Laskov, Klaus-Robert Müller, Alexander Zien, Sören Sonnenburg

Occlusive Components Analysis Jörg Lücke, Richard Turner, Maneesh Sahani, Marc Henniges

Distribution-Calibrated Hierarchical Classification Ofer Dekel

A Smoothed Approximate Linear Program Vijay Desai, Vivek Farias, Ciamac C. Moallemi

Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model Ed Vul, George Alvarez, Joshua Tenenbaum, Michael Black

Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han

Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models Ryan Mcdonald, Mehryar Mohri, Nathan Silberman, Dan Walker, Gideon Mann

On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation Saketha Jagarlapudi, Dinesh G, Raman S, Chiranjib Bhattacharyya, Aharon Ben-tal, Ramakrishnan K.r.

Estimating image bases for visual image reconstruction from human brain activity Yusuke Fujiwara, Yoichi Miyawaki, Yukiyasu Kamitani

A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers Sahand Negahban, Bin Yu, Martin J. Wainwright, Pradeep Ravikumar

Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction Grzegorz Swirszcz, Naoki Abe, Aurelie C. Lozano

Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander Gray

Online Learning of Assignments Matthew Streeter, Daniel Golovin, Andreas Krause

Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining George Konidaris, Andrew Barto

Strategy Grafting in Extensive Games Kevin Waugh, Nolan Bard, Michael Bowling

Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum, Michael Black

Learning a Small Mixture of Trees M. Kumar, Daphne Koller

An Additive Latent Feature Model for Transparent Object Recognition Mario Fritz, Gary Bradski, Sergey Karayev, Trevor Darrell, Michael Black

Know Thy Neighbour: A Normative Theory of Synaptic Depression Jean-pascal Pfister, Peter Dayan, Máté Lengyel

Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs Alexandre Bouchard-côté, Slav Petrov, Dan Klein

A Rate Distortion Approach for Semi-Supervised Conditional Random Fields Yang Wang, Gholamreza Haffari, Shaojun Wang, Greg Mori

Learning to Explore and Exploit in POMDPs Chenghui Cai, Xuejun Liao, Lawrence Carin

Multiple Incremental Decremental Learning of Support Vector Machines Masayuki Karasuyama, Ichiro Takeuchi

Bayesian Source Localization with the Multivariate Laplace Prior Marcel Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes

Learning Non-Linear Combinations of Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

Conditional Neural Fields Jian Peng, Liefeng Bo, Jinbo Xu

An Online Algorithm for Large Scale Image Similarity Learning Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio

Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning Steven Chase, Andrew Schwartz, Wolfgang Maass, Robert Legenstein

The Infinite Partially Observable Markov Decision Process Finale Doshi-velez

Accelerated Gradient Methods for Stochastic Optimization and Online Learning Chonghai Hu, Weike Pan, James Kwok

Robust Value Function Approximation Using Bilinear Programming Marek Petrik, Shlomo Zilberstein

Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units Feng Yan, Ningyi Xu, Yuan Qi

Local Rules for Global MAP: When Do They Work ? Kyomin Jung, Pushmeet Kohli, Devavrat Shah

Bayesian estimation of orientation preference maps Sebastian Gerwinn, Leonard White, Matthias Kaschube, Matthias Bethge, Jakob H. Macke

A Bayesian Analysis of Dynamics in Free Recall Richard Socher, Samuel Gershman, Per Sederberg, Kenneth Norman, Adler Perotte, David Blei

Structural inference affects depth perception in the context of potential occlusion Ian Stevenson, Konrad Koerding

Indian Buffet Processes with Power-law Behavior Yee Teh, Dilan Gorur

Boosting with Spatial Regularization Yongxin Xi, Uri Hasson, Peter J. Ramadge, Zhen Xiang

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

Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction Kwang Kim, Florian Steinke, Matthias Hein

Localizing Bugs in Program Executions with Graphical Models Laura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer

Human Rademacher Complexity Jerry Zhu, Bryan Gibson, Timothy T. Rogers

Beyond Convexity: Online Submodular Minimization Elad Hazan, Satyen Kale

Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization Massih R. Amini, Nicolas Usunier, Cyril Goutte

Measuring model complexity with the prior predictive Wolf Vanpaemel

Nonparametric Bayesian Texture Learning and Synthesis Long Zhu, Yuanahao Chen, Bill Freeman, Antonio Torralba

A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation Lan Du, Lu Ren, Lawrence Carin, David Dunson

Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise Jacob Whitehill, Ting-fan Wu, Jacob Bergsma, Javier Movellan, Paul Ruvolo

Reading Tea Leaves: How Humans Interpret Topic Models Jonathan Chang, Sean Gerrish, Chong Wang, Jordan Boyd-graber, David Blei

Segmenting Scenes by Matching Image Composites Bryan Russell, Alyosha Efros, Josef Sivic, Bill Freeman, Andrew Zisserman

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

Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition Ashish Kapoor, Eric Horvitz

An Integer Projected Fixed Point Method for Graph Matching and MAP Inference Marius Leordeanu, Martial Hebert, Rahul Sukthankar

Efficient Bregman Range Search Lawrence Cayton

Complexity of Decentralized Control: Special Cases Martin Allen, Shlomo Zilberstein

Advances in Neural Information Processing Systems 22 (NIPS 2009)

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