NIPS 2009 Proceedings

Advances in Neural Information Processing Systems 22 (NIPS 2009)

The papers below appear in Advances in Neural Information Processing Systems 22 edited by Y. Bengio and D. Schuurmans and J.D. Lafferty and C.K.I. Williams and A. Culotta.
They are proceedings from the conference, "Neural Information Processing Systems 2009."

Information-theoretic lower bounds on the oracle complexity of convex optimization Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett, Pradeep K. Ravikumar
Streaming k-means approximation Nir Ailon, Ragesh Jaiswal, Claire Monteleoni
Complexity of Decentralized Control: Special Cases Martin Allen, Shlomo Zilberstein
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization Massih Amini, Nicolas Usunier, Cyril Goutte
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection Roy Anati, Kostas Daniilidis
Data-driven calibration of linear estimators with minimal penalties Sylvain Arlot, Francis R. Bach
On Learning Rotations Raman Arora
Polynomial Semantic Indexing Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution Cosmin Bejan, Matthew Titsworth, Andrew Hickl, Sanda Harabagiu
Group Sparse Coding Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow
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 S. Bergstra
No evidence for active sparsification in the visual cortex Pietro Berkes, Ben White, Jozsef Fiser
Manifold Regularization for SIR with Rate Root-n Convergence Wei Bian, Dacheng Tao
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity Andreas Bartels, Matthew Blaschko, Jacquelyn A. Shelton
Efficient Match Kernel between Sets of Features for Visual Recognition Liefeng Bo, Cristian Sminchisescu
Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs Alexandre Bouchard-côté, Slav Petrov, Dan Klein
Unsupervised Feature Selection for the k-means Clustering Problem Christos Boutsidis, Petros Drineas, Michael W. Mahoney
On Invariance in Hierarchical Models Jake Bouvrie, Lorenzo Rosasco, Tomaso Poggio
Nash Equilibria of Static Prediction Games Michael Brückner, Tobias Scheffer
Optimal context separation of spiking haptic signals by second-order somatosensory neurons Romain Brasselet, Roland Johansson, Angelo Arleo
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability Keith Bush, Joelle Pineau
Learning to Explore and Exploit in POMDPs Chenghui Cai, Xuejun Liao, Lawrence Carin
Speaker Comparison with Inner Product Discriminant Functions Zahi Karam, Douglas Sturim, William M. Campbell
A Stochastic approximation method for inference in probabilistic graphical models Peter Carbonetto, Matthew King, Firas Hamze
Bayesian Nonparametric Models on Decomposable Graphs Francois Caron, Arnaud Doucet
Adaptive Design Optimization in Experiments with People Daniel Cavagnaro, Jay Myung, Mark A. Pitt
Efficient Bregman Range Search Lawrence Cayton
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 A. Cecchi
Learning with Compressible Priors Volkan Cevher
Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis Barry Chai, Dirk Walther, Diane Beck, Li Fei-fei
Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes Kian M. Chai
Reading Tea Leaves: How Humans Interpret Topic Models Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber, David M. Blei
A Parameter-free Hedging Algorithm Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu
An Online Algorithm for Large Scale Image Similarity Learning Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio
Ranking Measures and Loss Functions in Learning to Rank Wei Chen, Tie-yan Liu, Yanyan Lan, Zhi-ming Ma, Hang Li
Factor Modeling for Advertisement Targeting Ye Chen, Michael Kapralov, John Canny, Dmitry Y. Pavlov
The Ordered Residual Kernel for Robust Motion Subspace Clustering Tat-jun Chin, Hanzi Wang, David Suter
Kernel Methods for Deep Learning Youngmin Cho, Lawrence K. Saul
Approximating MAP by Compensating for Structural Relaxations Arthur Choi, Adnan Darwiche
AUC optimization and the two-sample problem Nicolas Vayatis, Marine Depecker, Stéphan J. Clémençcon
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing Ruben Coen-cagli, Peter Dayan, Odelia Schwartz
fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity Bryan Conroy, Ben Singer, James Haxby, Peter J. Ramadge
Sensitivity analysis in HMMs with application to likelihood maximization Pierre-arnaud Coquelin, Romain Deguest, Rémi Munos
Learning Non-Linear Combinations of Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism Douglas Eck, Yoshua Bengio, Aaron C. Courville
Adaptive Regularization of Weight Vectors Koby Crammer, Alex Kulesza, Mark Dredze
Learning transport operators for image manifolds Benjamin Culpepper, Bruno A. Olshausen
White Functionals for Anomaly Detection in Dynamical Systems Marco Cuturi, Jean-philippe Vert, Alexandre D'aspremont
L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry Arnak Dalalyan, Renaud Keriven
Distribution-Calibrated Hierarchical Classification Ofer Dekel
A Smoothed Approximate Linear Program Vijay Desai, Vivek Farias, Ciamac C. Moallemi
Localizing Bugs in Program Executions with Graphical Models Laura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer
The Infinite Partially Observable Markov Decision Process Finale Doshi-velez
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation Lan Du, Lu Ren, Lawrence Carin, David B. Dunson
Efficient Learning using Forward-Backward Splitting Yoram Singer, John C. Duchi
A Data-Driven Approach to Modeling Choice Vivek Farias, Srikanth Jagabathula, Devavrat Shah
Subject independent EEG-based BCI decoding Siamac Fazli, Cristian Grozea, Marton Danoczy, Benjamin Blankertz, Florin Popescu, Klaus-Robert Müller
Semi-Supervised Learning in Gigantic Image Collections Rob Fergus, Yair Weiss, Antonio Torralba
Evaluating multi-class learning strategies in a generative hierarchical framework for object detection Sanja Fidler, Marko Boben, Ales Leonardis
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis Sundeep Rangan, Alyson K. Fletcher
Sharing Features among Dynamical Systems with Beta Processes Emily Fox, Michael I. Jordan, Erik B. Sudderth, Alan S. Willsky
An Additive Latent Feature Model for Transparent Object Recognition Mario Fritz, Gary Bradski, Sergey Karayev, Trevor Darrell, Michael J. Black
An LP View of the M-best MAP problem Menachem Fromer, Amir Globerson
Estimating image bases for visual image reconstruction from human brain activity Yusuke Fujiwara, Yoichi Miyawaki, Yukiyasu Kamitani
Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han
Lattice Regression Eric Garcia, Maya Gupta
From PAC-Bayes Bounds to KL Regularization Pascal Germain, Alexandre Lacasse, Mario Marchand, Sara Shanian, François Laviolette
Perceptual Multistability as Markov Chain Monte Carlo Inference Samuel Gershman, Ed Vul, Joshua B. Tenenbaum
A joint maximum-entropy model for binary neural population patterns and continuous signals Sebastian Gerwinn, Philipp Berens, Matthias Bethge
A Biologically Plausible Model for Rapid Natural Scene Identification Sennay Ghebreab, Steven Scholte, Victor Lamme, Arnold Smeulders
A Gaussian Tree Approximation for Integer Least-Squares Jacob Goldberger, Amir Leshem
Measuring Invariances in Deep Networks Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe, Andrew Y. Ng
Region-based Segmentation and Object Detection Stephen Gould, Tianshi Gao, Daphne Koller
Posterior vs Parameter Sparsity in Latent Variable Models Kuzman Ganchev, Ben Taskar, Fernando Pereira, João Gama
A Fast, Consistent Kernel Two-Sample Test Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur
Non-stationary continuous dynamic Bayesian networks Marco Grzegorczyk, Dirk Husmeier
Label Selection on Graphs Andrew Guillory, Jeff A. Bilmes
Beyond Convexity: Online Submodular Minimization Elad Hazan, Satyen Kale
On Stochastic and Worst-case Models for Investing Elad Hazan, Satyen Kale
Robust Nonparametric Regression with Metric-Space Valued Output Matthias Hein
Hierarchical Learning of Dimensional Biases in Human Categorization Adam Sanborn, Nick Chater, Katherine A. Heller
Bayesian Sparse Factor Models and DAGs Inference and Comparison Ricardo Henao, Ole Winther
Sparse and Locally Constant Gaussian Graphical Models Jean Honorio, Dimitris Samaras, Nikos Paragios, Rita Goldstein, Luis E. Ortiz
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning Anne Hsu, Thomas L. Griffiths
Periodic Step Size Adaptation for Single Pass On-line Learning Chun-nan Hsu, Yu-ming Chang, Hanshen Huang, Yuh-jye Lee
Multi-Label Prediction via Compressed Sensing John Langford, Tong Zhang, Daniel J. Hsu, Sham M. Kakade
Accelerated Gradient Methods for Stochastic Optimization and Online Learning Chonghai Hu, Weike Pan, James T. Kwok
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) Tao Hu, Anthony Leonardo, Dmitri B. Chklovskii
Riffled Independence for Ranked Data Jonathan Huang, Carlos Guestrin
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
Discrete MDL Predicts in Total Variation Marcus Hutter
Particle-based Variational Inference for Continuous Systems Andrew Frank, Padhraic Smyth, Alexander T. Ihler
Modeling Social Annotation Data with Content Relevance using a Topic Model Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
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, Ramakrishnan K.r.
Bayesian Belief Polarization Alan Jern, Kai-min Chang, Charles Kemp
Regularized Distance Metric Learning:Theory and Algorithm Rong Jin, Shijun Wang, Yang Zhou
Local Rules for Global MAP: When Do They Work ? Kyomin Jung, Pushmeet Kohli, Devavrat Shah
Potential-Based Agnostic Boosting Varun Kanade, Adam Kalai
Directed Regression Yi-hao Kao, Benjamin V. Roy, Xiang Yan
Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition Ashish Kapoor, Eric Horvitz
Multiple Incremental Decremental Learning of Support Vector Machines Masayuki Karasuyama, Ichiro Takeuchi
Submodularity Cuts and Applications Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes
Individuation, Identification and Object Discovery Charles Kemp, Alan Jern, Fei Xu
Abstraction and Relational learning Charles Kemp, Alan Jern
Quantification and the language of thought Charles Kemp
Matrix Completion from Noisy Entries Raghunandan Keshavan, Andrea Montanari, Sewoong Oh
Unsupervised Detection of Regions of Interest Using Iterative Link Analysis Gunhee Kim, Antonio Torralba
Clustering sequence sets for motif discovery Jong K. Kim, Seungjin Choi
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction Kwang I. Kim, Florian Steinke, Matthias Hein
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks Stefan Klampfl, Wolfgang Maass
Efficient and Accurate Lp-Norm Multiple Kernel Learning Marius Kloft, Ulf Brefeld, Pavel Laskov, Klaus-Robert Müller, Alexander Zien, Sören Sonnenburg
Sparsistent Learning of Varying-coefficient Models with Structural Changes Mladen Kolar, Le Song, Eric P. Xing
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining George Konidaris, Andre S. Barreto
Fast, smooth and adaptive regression in metric spaces Samory Kpotufe
Fast Image Deconvolution using Hyper-Laplacian Priors Dilip Krishnan, Rob Fergus
Learning to Hash with Binary Reconstructive Embeddings Brian Kulis, Trevor Darrell
Learning a Small Mixture of Trees M. P. Kumar, Daphne Koller
Ensemble Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
Occlusive Components Analysis Jörg Lücke, Richard Turner, Maneesh Sahani, Marc Henniges
Monte Carlo Sampling for Regret Minimization in Extensive Games Marc Lanctot, Kevin Waugh, Martin Zinkevich, Michael Bowling
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features Anibal Figueiras-vidal, Miguel Lázaro-Gredilla
Unsupervised feature learning for audio classification using convolutional deep belief networks Honglak Lee, Peter Pham, Yan Largman, Andrew Y. Ng
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning Steven Chase, Andrew Schwartz, Wolfgang Maass, Robert A. Legenstein
An Integer Projected Fixed Point Method for Graph Matching and MAP Inference Marius Leordeanu, Martial Hebert, Rahul Sukthankar
Probabilistic Relational PCA Wu-jun Li, Dit-Yan Yeung, Zhihua Zhang
Asymptotically Optimal Regularization in Smooth Parametric Models Percy S. Liang, Guillaume Bouchard, Francis R. Bach, Michael I. Jordan
Nonparametric Greedy Algorithms for the Sparse Learning Problem Han Liu, Xi Chen
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction Grzegorz Swirszcz, Naoki Abe, Aurelie C. Lozano
Modeling the spacing effect in sequential category learning Hongjing Lu, Matthew Weiden, Alan L. Yuille
Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation Jie Luo, Barbara Caputo, Vittorio Ferrari
Variational Gaussian-process factor analysis for modeling spatio-temporal data Jaakko Luttinen, Alexander Ilin
Solving Stochastic Games Liam M. Dermed, Charles L. Isbell
Bayesian estimation of orientation preference maps Sebastian Gerwinn, Leonard White, Matthias Kaschube, Matthias Bethge, Jakob H. Macke
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton, Hamid R. Maei, Csaba Szepesvári
Compressed Least-Squares Regression Odalric Maillard, Rémi Munos
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships Tomasz Malisiewicz, Alyosha Efros
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models Ryan Mcdonald, Mehryar Mohri, Nathan Silberman, Dan Walker, Gideon S. Mann
Toward Provably Correct Feature Selection in Arbitrary Domains Dimitris Margaritis
FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs Andrew McCallum, Karl Schultz, Sameer Singh
Matrix Completion from Power-Law Distributed Samples Raghu Meka, Prateek Jain, Inderjit S. Dhillon
Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out Yicong Meng, Bertram E. Shi
Nonparametric Latent Feature Models for Link Prediction Kurt Miller, Michael I. Jordan, Thomas L. Griffiths
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models Baback Moghaddam, Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process Finale Doshi-velez, Shakir Mohamed, Zoubin Ghahramani, David A. Knowles
Which graphical models are difficult to learn? Andrea Montanari, Jose A. Pereira
A Generalized Natural Actor-Critic Algorithm Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory Harold Pashler, Nicholas Cepeda, Robert V. Lindsey, Ed Vul, Michael C. Mozer
Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data Boaz Nadler, Nathan Srebro, Xueyuan Zhou
3D Object Recognition with Deep Belief Nets Vinod Nair, Geoffrey E. Hinton
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers Sahand Negahban, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar
STDP enables spiking neurons to detect hidden causes of their inputs Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
Noisy Generalized Binary Search Robert Nowak
Submanifold density estimation Arkadas Ozakin, Alexander G. Gray
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies Arno Onken, Steffen Grünewälder, Klaus Obermayer
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations Peter Orbanz
Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition Tom Ouyang, Randall Davis
Zero-shot Learning with Semantic Output Codes Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell
Conditional Neural Fields Jian Peng, Liefeng Bo, Jinbo Xu
Free energy score space Alessandro Perina, Marco Cristani, Umberto Castellani, Vittorio Murino, Nebojsa Jojic
Maximum likelihood trajectories for continuous-time Markov chains Theodore J. Perkins
Robust Value Function Approximation Using Bilinear Programming Marek Petrik, Shlomo Zilberstein
Exponential Family Graph Matching and Ranking James Petterson, Jin Yu, Julian J. Mcauley, Tibério S. Caetano
Know Thy Neighbour: A Normative Theory of Synaptic Depression Jean-pascal Pfister, Peter Dayan, Máté Lengyel
Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models Jonathan W. Pillow
Bilinear classifiers for visual recognition Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes
Convex Relaxation of Mixture Regression with Efficient Algorithms Novi Quadrianto, John Lim, Dale Schuurmans, Tibério S. Caetano
Distribution Matching for Transduction Novi Quadrianto, James Petterson, Alex J. Smola
Locality-sensitive binary codes from shift-invariant kernels Maxim Raginsky, Svetlana Lazebnik
Multi-Label Prediction via Sparse Infinite CCA Piyush Rai, Hal Daume
Linear-time Algorithms for Pairwise Statistical Problems Parikshit Ram, Dongryeol Lee, William March, Alexander G. Gray
Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing Sundeep Rangan, Vivek Goyal, Alyson K. Fletcher
Spatial Normalized Gamma Processes Vinayak Rao, Yee W. Teh
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness Garvesh Raskutti, Bin Yu, Martin J. Wainwright
A Game-Theoretic Approach to Hypergraph Clustering Samuel R. Bulò, Marcello Pelillo
Segmenting Scenes by Matching Image Composites Bryan Russell, Alyosha Efros, Josef Sivic, Bill Freeman, Andrew Zisserman
Filtering Abstract Senses From Image Search Results Kate Saenko, Trevor Darrell
Learning in Markov Random Fields using Tempered Transitions Ruslan R. Salakhutdinov
Replicated Softmax: an Undirected Topic Model Geoffrey E. Hinton, Ruslan R. Salakhutdinov
Learning models of object structure Joseph Schlecht, Kobus Barnard
Linearly constrained Bayesian matrix factorization for blind source separation Mikkel Schmidt
Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing Matthias Seeger
Improving Existing Fault Recovery Policies Guy Shani, Christopher Meek
Positive Semidefinite Metric Learning with Boosting Chunhua Shen, Junae Kim, Lei Wang, Anton Hengel
Fast subtree kernels on graphs Nino Shervashidze, Karsten M. Borgwardt
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling Lei Shi, Thomas L. Griffiths
Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition Natasha Singh-miller, Michael Collins
Semi-supervised Learning using Sparse Eigenfunction Bases Kaushik Sinha, Mikhail Belkin
Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions Matthias Bethge, Eero P. Simoncelli, Fabian H. Sinz
A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds Paris Smaragdis, Madhusudana Shashanka, Bhiksha Raj
A Bayesian Analysis of Dynamics in Free Recall Richard Socher, Samuel Gershman, Per Sederberg, Kenneth Norman, Adler J. Perotte, David M. Blei
Kernels and learning curves for Gaussian process regression on random graphs Peter Sollich, Matthew Urry, Camille Coti
Time-Varying Dynamic Bayesian Networks Le Song, Mladen Kolar, Eric P. Xing
Code-specific policy gradient rules for spiking neurons Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions Kenji Fukumizu, Arthur Gretton, Gert R. Lanckriet, Bernhard Schölkopf, Bharath K. Sriperumbudur
On the Convergence of the Concave-Convex Procedure Gert R. Lanckriet, Bharath K. Sriperumbudur
Fast Learning from Non-i.i.d. Observations Ingo Steinwart, Andreas Christmann
Structural inference affects depth perception in the context of potential occlusion Ian Stevenson, Konrad Koerding
The Wisdom of Crowds in the Recollection of Order Information Mark Steyvers, Brent Miller, Pernille Hemmer, Michael D. Lee
Online Learning of Assignments Matthew Streeter, Daniel Golovin, Andreas Krause
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification Amarnag Subramanya, Jeff A. Bilmes
Efficient Recovery of Jointly Sparse Vectors Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye
Modelling Relational Data using Bayesian Clustered Tensor Factorization Ilya Sutskever, Joshua B. Tenenbaum, Ruslan R. Salakhutdinov
Adapting to the Shifting Intent of Search Queries Umar Syed, Aleksandrs Slivkins, Nina Mishra
Indian Buffet Processes with Power-law Behavior Yee W. Teh, Dilan Gorur
Nonlinear directed acyclic structure learning with weakly additive noise models Arthur Gretton, Peter Spirtes, Robert E. Tillman
Compositionality of optimal control laws Emanuel Todorov
Maximin affinity learning of image segmentation Kevin Briggman, Winfried Denk, Sebastian Seung, Moritz N. Helmstaedter, Srinivas C. Turaga
Help or Hinder: Bayesian Models of Social Goal Inference Tomer Ullman, Chris Baker, Owen Macindoe, Owain Evans, Noah Goodman, Joshua B. Tenenbaum
Learning to Rank by Optimizing NDCG Measure Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao
Streaming Pointwise Mutual Information Benjamin V. Durme, Ashwin Lall
Bayesian Source Localization with the Multivariate Laplace Prior Marcel V. Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes
Gaussian process regression with Student-t likelihood Jarno Vanhatalo, Pasi Jylänki, Aki Vehtari
Measuring model complexity with the prior predictive Wolf Vanpaemel
Structured output regression for detection with partial truncation Andrea Vedaldi, Andrew Zisserman
Bootstrapping from Game Tree Search Joel Veness, David Silver, Alan Blair, William Uther
Tracking Dynamic Sources of Malicious Activity at Internet Scale Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck
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
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming Xiao-ming Wu, Anthony M. So, Zhenguo Li, Shuo-yen R. Li
Rethinking LDA: Why Priors Matter Hanna M. Wallach, David M. Mimno, Andrew McCallum
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process Chong Wang, David M. Blei
Variational Inference for the Nested Chinese Restaurant Process Chong Wang, David M. Blei
Sufficient Conditions for Agnostic Active Learnable Liwei Wang
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields Yang Wang, Gholamreza Haffari, Shaojun Wang, Greg Mori
Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation Yusuke Watanabe, Kenji Fukumizu
Strategy Grafting in Extensive Games Kevin Waugh, Nolan Bard, Michael Bowling
Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise Jacob Whitehill, Ting-fan Wu, Jacob Bergsma, Javier R. Movellan, Paul L. Ruvolo
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum, Michael J. Black
Sequential effects reflect parallel learning of multiple environmental regularities Matthew Wilder, Matt Jones, Michael C. Mozer
A Neural Implementation of the Kalman Filter Robert Wilson, Leif Finkel
Sparse Estimation Using General Likelihoods and Non-Factorial Priors David P. Wipf, Srikantan S. Nagarajan
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization John Wright, Arvind Ganesh, Shankar Rao, Yigang Peng, Yi Ma
Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering Lei Wu, Rong Jin, Steven C. Hoi, Jianke Zhu, Nenghai Yu
Statistical Consistency of Top-k Ranking Fen Xia, Tie-yan Liu, Hang Li
Boosting with Spatial Regularization Yongxin Xi, Uri Hasson, Peter J. Ramadge, Zhen J. Xiang
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization Lin Xiao
Adaptive Regularization for Transductive Support Vector Machine Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu, Zhirong Yang
Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units Feng Yan, Ningyi Xu, Yuan Qi
Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora Shuang-hong Yang, Hongyuan Zha, Bao-gang Hu
Heterogeneous multitask learning with joint sparsity constraints Xiaolin Yang, Seyoung Kim, Eric P. Xing
Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording Zhi Yang, Qi Zhao, Edward Keefer, Wentai Liu
Heavy-Tailed Symmetric Stochastic Neighbor Embedding Zhirong Yang, Irwin King, Zenglin Xu, Erkki Oja
Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions Bangpeng Yao, Dirk Walther, Diane Beck, Li Fei-fei
Multi-Step Dyna Planning for Policy Evaluation and Control Hengshuai Yao, Shalabh Bhatnagar, Dongcui Diao, Richard S. Sutton, Csaba Szepesvári
Conditional Random Fields with High-Order Features for Sequence Labeling Nan Ye, Wee S. Lee, Hai L. Chieu, Dan Wu
Analysis of SVM with Indefinite Kernels Yiming Ying, Colin Campbell, Mark Girolami
Sparse Metric Learning via Smooth Optimization Yiming Ying, Kaizhu Huang, Colin Campbell
Nonlinear Learning using Local Coordinate Coding Kai Yu, Tong Zhang, Yihong Gong
A General Projection Property for Distribution Families Yao-liang Yu, Yuxi Li, Dale Schuurmans, Csaba Szepesvári
Optimal Scoring for Unsupervised Learning Zhihua Zhang, Guang Dai
Anomaly Detection with Score functions based on Nearest Neighbor Graphs Manqi Zhao, Venkatesh Saligrama
DUOL: A Double Updating Approach for Online Learning Peilin Zhao, Steven C. Hoi, Rong Jin
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification Wenming Zheng, Zhouchen Lin
Efficient Moments-based Permutation Tests Chunxiao Zhou, Huixia J. Wang, Yongmei M. Wang
Canonical Time Warping for Alignment of Human Behavior Feng Zhou, Fernando Torre
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations Mingyuan Zhou, Haojun Chen, Lu Ren, Guillermo Sapiro, Lawrence Carin, John W. Paisley
Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation Shuheng Zhou
Nonparametric Bayesian Texture Learning and Synthesis Long Zhu, Yuanahao Chen, Bill Freeman, Antonio Torralba
Human Rademacher Complexity Xiaojin Zhu, Bryan R. Gibson, Timothy T. Rogers
Slow Learners are Fast Martin Zinkevich, John Langford, Alex J. Smola
The 'tree-dependent components' of natural scenes are edge filters Daniel Zoran, Yair Weiss