Advances in Neural Information Processing Systems 22

NIPS 2009

Edited by Y. Bengio and D. Schuurmans and J. Lafferty and C. Williams and A. Culotta

ISBN: 9781615679119

262 papers

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 C. 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 S. 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 W. 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 V. Roy, Xiang Yan
Nonparametric Greedy Algorithms for the Sparse Learning Problem Han Liu, Xi Chen
Rethinking LDA: Why Priors Matter Hanna M. Wallach, David M. Mimno, Andrew McCallum
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity Andreas Bartels, Matthew Blaschko, Jacquelyn A. Shelton
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning Anne Hsu, Thomas L. 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 C. 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 V. 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 Y. Pavlov
Sparse Estimation Using General Likelihoods and Non-Factorial Priors David P. Wipf, Srikantan S. 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 A. Knowles
Matrix Completion from Power-Law Distributed Samples Raghu Meka, Prateek Jain, Inderjit S. 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 A. Pereira
Information-theoretic lower bounds on the oracle complexity of convex optimization Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett, Pradeep K. Ravikumar
Linear-time Algorithms for Pairwise Statistical Problems Parikshit Ram, Dongryeol Lee, William March, Alexander G. 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 G. 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 J. 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 C. 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, Ruslan 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 Hamid R. Maei, Csaba Szepesvári, Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton
Group Sparse Coding Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process Chong Wang, David M. 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 J. Clémençcon
Measuring Invariances in Deep Networks Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe, Andrew Y. Ng
Nonparametric Latent Feature Models for Link Prediction Kurt Miller, Michael I. Jordan, Thomas L. Griffiths
Asymptotically Optimal Regularization in Smooth Parametric Models Percy Liang, Guillaume Bouchard, Francis R. Bach, Michael I. 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 B. Fox, Michael I. Jordan, Erik B. Sudderth, Alan S. Willsky
The Wisdom of Crowds in the Recollection of Order Information Mark Steyvers, Brent Miller, Pernille Hemmer, Michael D. 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 K. 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 B. Tenenbaum
Sequential effects reflect parallel learning of multiple environmental regularities Matthew Wilder, Matt Jones, Michael Mozer
Noisy Generalized Binary Search Robert Nowak
Solving Stochastic Games Liam M. Dermed, Charles L. Isbell
Modelling Relational Data using Bayesian Clustered Tensor Factorization Ilya Sutskever, Joshua B. Tenenbaum, Ruslan Salakhutdinov
Kernel Methods for Deep Learning Youngmin Cho, Lawrence K. 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 P. 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 T. 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 R. 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 N. Helmstaedter, Srinivas C. Turaga
Perceptual Multistability as Markov Chain Monte Carlo Inference Samuel Gershman, Ed Vul, Joshua B. 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 Lindsey, Ed Vul, Michael Mozer
A Game-Theoretic Approach to Hypergraph Clustering Samuel R. 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 A. 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 S. 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 L. 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 A. Cecchi
Sparsistent Learning of Varying-coefficient Models with Structural Changes Mladen Kolar, Le Song, Eric P. 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 E. 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 J. Mcauley, Tibério S. Caetano
Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out Yicong Meng, Bertram E. 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 R. 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 B. 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 S. Lee, Hai L. 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 M. So, Zhenguo Li, Shuo-yen R. 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 R. 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 Y. Ng
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models Baback Moghaddam, Mohammad Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin
Learning transport operators for image manifolds Benjamin Culpepper, Bruno A. 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 P. 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 J. Wang, Yongmei M. Wang
Maximum likelihood trajectories for continuous-time Markov chains Theodore J. 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 J. 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 Ruslan 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 M. 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 P. Simoncelli, Fabian H. 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 M. 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 W. 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 B. Tenenbaum, Michael J. 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 S. Mann
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.
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 K. 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 G. Gray
Online Learning of Assignments Matthew Streeter, Daniel Golovin, Andreas Krause
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining George Konidaris, Andrew G. 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 J. Black
Learning a Small Mixture of Trees M. P. Kumar, Daphne Koller
An Additive Latent Feature Model for Transparent Object Recognition Mario Fritz, Gary Bradski, Sergey Karayev, Trevor Darrell, Michael J. 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 V. 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 A. 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 T. 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 J. Perotte, David M. Blei
Structural inference affects depth perception in the context of potential occlusion Ian Stevenson, Konrad Koerding
Indian Buffet Processes with Power-law Behavior Yee W. Teh, Dilan Gorur
Boosting with Spatial Regularization Yongxin Xi, Uri Hasson, Peter J. Ramadge, Zhen J. Xiang
Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models Jonathan W. Pillow
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction Kwang I. Kim, Florian Steinke, Matthias Hein
Localizing Bugs in Program Executions with Graphical Models Laura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer
Human Rademacher Complexity Xiaojin Zhu, Bryan R. 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 B. Dunson
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
Reading Tea Leaves: How Humans Interpret Topic Models Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber, David M. 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 M. 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

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