NeurIPS 2009

262 papers

Unsupervised feature learning for audio classification using convolutional deep belief networks

Honglak Lee, Peter Pham, Yan Largman, Andrew Y. Ng

fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity

Bryan Conroy, Ben Singer, James Haxby, Peter J. Ramadge

Data-driven calibration of linear estimators with minimal penalties

Sylvain Arlot, Francis R. Bach

A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds

Paris Smaragdis, Madhusudana Shashanka, Bhiksha Raj

Bayesian Sparse Factor Models and DAGs Inference and Comparison

Ricardo Henao, Ole Winther

Submodularity Cuts and Applications

Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes

Anomaly Detection with Score functions based on Nearest Neighbor Graphs

Manqi Zhao, Venkatesh Saligrama

A Data-Driven Approach to Modeling Choice

Vivek Farias, Srikanth Jagabathula, Devavrat Shah

Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming

Xiao-ming Wu, Anthony M. So, Zhenguo Li, Shuo-yen R. Li

Abstraction and Relational learning

Charles Kemp, Alan Jern

Conditional Random Fields with High-Order Features for Sequence Labeling

Nan Ye, Wee S. Lee, Hai L. Chieu, Dan Wu

Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships

Tomasz Malisiewicz, Alyosha Efros

Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation

Shuheng Zhou

Kernels and learning curves for Gaussian process regression on random graphs

Peter Sollich, Matthew Urry, Camille Coti

Robust Nonparametric Regression with Metric-Space Valued Output

Matthias Hein

A Fast, Consistent Kernel Two-Sample Test

Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur

Label Selection on Graphs

Andrew Guillory, Jeff A. Bilmes

Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME)

Tao Hu, Anthony Leonardo, Dmitri B. Chklovskii

Posterior vs Parameter Sparsity in Latent Variable Models

Kuzman Ganchev, Ben Taskar, Fernando Pereira, João Gama

Adaptive Regularization of Weight Vectors

Koby Crammer, Alex Kulesza, Mark Dredze

Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording

Zhi Yang, Qi Zhao, Edward Keefer, Wentai Liu

Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis

Sundeep Rangan, Alyson K. Fletcher

On the Convergence of the Concave-Convex Procedure

Gert R. Lanckriet, Bharath K. Sriperumbudur

Subject independent EEG-based BCI decoding

Siamac Fazli, Cristian Grozea, Marton Danoczy, Benjamin Blankertz, Florin Popescu

Adaptive Regularization for Transductive Support Vector Machine

Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu

Construction of Nonparametric Bayesian Models from Parametric Bayes Equations

Peter Orbanz

Periodic Step Size Adaptation for Single Pass On-line Learning

Chun-nan Hsu, Yu-ming Chang, Hanshen Huang, Yuh-jye Lee

Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out

Yicong Meng, Bertram E. Shi

Exponential Family Graph Matching and Ranking

James Petterson, Jin Yu, Julian J. Mcauley, Tibério S. Caetano

FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs

Andrew McCallum, Karl Schultz, Sameer Singh

Nonlinear directed acyclic structure learning with weakly additive noise models

Arthur Gretton, Peter Spirtes, Robert E. Tillman

A Gaussian Tree Approximation for Integer Least-Squares

Jacob Goldberger, Amir Leshem

On Learning Rotations

Raman Arora

Semi-supervised Learning using Sparse Eigenfunction Bases

Kaushik Sinha, Mikhail Belkin

Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis

Barry Chai, Dirk Walther, Diane Beck, Li Fei-fei

Quantification and the language of thought

Charles Kemp

Analysis of SVM with Indefinite Kernels

Yiming Ying, Colin Campbell, Mark Girolami

Dual Averaging Method for Regularized Stochastic Learning and Online Optimization

Lin Xiao

Sparsistent Learning of Varying-coefficient Models with Structural Changes

Mladen Kolar, Le Song, Eric P. Xing

Discriminative Network Models of Schizophrenia

Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-laure Paillere-martinot

Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling

Lei Shi, Thomas L. Griffiths

Polynomial Semantic Indexing

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa

Hierarchical Learning of Dimensional Biases in Human Categorization

Adam Sanborn, Nick Chater, Katherine A. Heller

Convex Relaxation of Mixture Regression with Efficient Algorithms

Novi Quadrianto, John Lim, Dale Schuurmans, Tibério S. Caetano

Improving Existing Fault Recovery Policies

Guy Shani, Christopher Meek

3D Object Recognition with Deep Belief Nets

Vinod Nair, Geoffrey E. Hinton

Toward Provably Correct Feature Selection in Arbitrary Domains

Dimitris Margaritis

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

Matthias Seeger

An LP View of the M-best MAP problem

Menachem Fromer, Amir Globerson

A Neural Implementation of the Kalman Filter

Robert Wilson, Leif Finkel

Riffled Independence for Ranked Data

Jonathan Huang, Carlos Guestrin

Adaptive Design Optimization in Experiments with People

Daniel Cavagnaro, Jay Myung, Mark A. Pitt

Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora

Shuang-hong Yang, Hongyuan Zha, Bao-gang Hu

A Game-Theoretic Approach to Hypergraph Clustering

Samuel R. Bulò, Marcello Pelillo

Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory

Harold Pashler, Nicholas Cepeda, Robert Lindsey, Ed Vul, Michael Mozer

Adapting to the Shifting Intent of Search Queries

Umar Syed, Aleksandrs Slivkins, Nina Mishra

Probabilistic Relational PCA

Wu-jun Li, Dit-Yan Yeung, Zhihua Zhang

Perceptual Multistability as Markov Chain Monte Carlo Inference

Samuel Gershman, Ed Vul, Joshua B. Tenenbaum

Maximin affinity learning of image segmentation

Kevin Briggman, Winfried Denk, Sebastian Seung, Moritz N. Helmstaedter, Srinivas C. Turaga

Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data

Boaz Nadler, Nathan Srebro, Xueyuan Zhou

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions

Kenji Fukumizu, Arthur Gretton, Gert R. Lanckriet, Bernhard Schölkopf, Bharath K. Sriperumbudur

Multi-Label Prediction via Compressed Sensing

Daniel J. Hsu, Sham M. Kakade, John Langford, Tong Zhang

Learning to Hash with Binary Reconstructive Embeddings

Brian Kulis, Trevor Darrell

L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry

Arnak Dalalyan, Renaud Keriven

Efficient Learning using Forward-Backward Splitting

Yoram Singer, John C. Duchi

Particle-based Variational Inference for Continuous Systems

Andrew Frank, Padhraic Smyth, Alexander T. Ihler

Inter-domain Gaussian Processes for Sparse Inference using Inducing Features

Miguel Lázaro-Gredilla, Aníbal Figueiras-Vidal

Learning with Compressible Priors

Volkan Cevher

Heterogeneous multitask learning with joint sparsity constraints

Xiaolin Yang, Seyoung Kim, Eric P. Xing

Optimal context separation of spiking haptic signals by second-order somatosensory neurons

Romain Brasselet, Roland Johansson, Angelo Arleo

Kernel Methods for Deep Learning

Youngmin Cho, Lawrence K. Saul

Modelling Relational Data using Bayesian Clustered Tensor Factorization

Ilya Sutskever, Joshua B. Tenenbaum, Ruslan Salakhutdinov

Solving Stochastic Games

Liam M. Dermed, Charles L Isbell, Charles L. Isbell

Noisy Generalized Binary Search

Robert Nowak

Sequential effects reflect parallel learning of multiple environmental regularities

Matthew Wilder, Matt Jones, Michael Mozer

Help or Hinder: Bayesian Models of Social Goal Inference

Tomer Ullman, Chris Baker, Owen Macindoe, Owain Evans, Noah Goodman

Streaming k-means approximation

Nir Ailon, Ragesh Jaiswal, Claire Monteleoni

Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies

Arno Onken, Steffen Grünewälder, Klaus Obermayer

Bayesian Nonparametric Models on Decomposable Graphs

Francois Caron, Arnaud Doucet

Clustering sequence sets for motif discovery

Jong K. Kim, Seungjin Choi

Efficient Match Kernel between Sets of Features for Visual Recognition

Liefeng Bo, Cristian Sminchisescu

Efficient Recovery of Jointly Sparse Vectors

Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye

The Wisdom of Crowds in the Recollection of Order Information

Mark Steyvers, Brent Miller, Pernille Hemmer, Michael D. Lee

Sharing Features among Dynamical Systems with Beta Processes

Emily B. Fox, Michael I. Jordan, Erik B. Sudderth, Alan S. Willsky

Lattice Regression

Eric Garcia, Maya Gupta

Variational Gaussian-process factor analysis for modeling spatio-temporal data

Jaakko Luttinen, Alexander Ilin

Asymptotically Optimal Regularization in Smooth Parametric Models

Percy Liang, Guillaume Bouchard, Francis R. Bach, Michael I. Jordan

Nonparametric Latent Feature Models for Link Prediction

Kurt Miller, Michael I. Jordan, Thomas L. Griffiths

Measuring Invariances in Deep Networks

Ian Goodfellow, Honglak Lee, Andrew Saxe, Andrew Y. Ng, Quoc V Le

AUC optimization and the two-sample problem

Nicolas Vayatis, Marine Depecker, Stéphan J. Clémençcon

Compositionality of optimal control laws

Emanuel Todorov

Fast Image Deconvolution using Hyper-Laplacian Priors

Dilip Krishnan, Rob Fergus

Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process

Chong Wang, David M. Blei

Group Sparse Coding

Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow

Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation

Hamid R. Maei, Csaba Szepesvári, Shalabh Bhatnagar, Doina Precup, David Silver

Modeling Social Annotation Data with Content Relevance using a Topic Model

Tomoharu Iwata, Takeshi Yamada, Naonori Ueda

Individuation, Identification and Object Discovery

Charles Kemp, Alan Jern, Fei Xu

Bootstrapping from Game Tree Search

Joel Veness, David Silver, Alan Blair, William Uther

The 'tree-dependent components' of natural scenes are edge filters

Daniel Zoran, Yair Weiss

Sparse Metric Learning via Smooth Optimization

Yiming Ying, Kaizhu Huang, Colin Campbell