NeurIPS 2009

262 papers

Sparse and Locally Constant Gaussian Graphical Models

Jean Honorio, Dimitris Samaras, Nikos Paragios, Rita Goldstein, Luis E. Ortiz

Linearly constrained Bayesian matrix factorization for blind source separation

Mikkel Schmidt

Bayesian Belief Polarization

Alan Jern, Kai-min Chang, Charles Kemp

Fast, smooth and adaptive regression in metric spaces

Samory Kpotufe

Replicated Softmax: an Undirected Topic Model

Geoffrey E. Hinton, Ruslan Salakhutdinov

Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection

Roy Anati, Kostas Daniilidis

Ranking Measures and Loss Functions in Learning to Rank

Wei Chen, Tie-yan Liu, Yanyan Lan, Zhi-ming Ma, Hang Li

Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering

Lei Wu, Rong Jin, Steven C. Hoi, Jianke Zhu, Nenghai Yu

A Parameter-free Hedging Algorithm

Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu

Canonical Time Warping for Alignment of Human Behavior

Feng Zhou, Fernando Torre

Distribution Matching for Transduction

Novi Quadrianto, James Petterson, Alex J. Smola

No evidence for active sparsification in the visual cortex

Pietro Berkes, Ben White, Jozsef Fiser

Nonlinear Learning using Local Coordinate Coding

Kai Yu, Tong Zhang, Yihong Gong

Submanifold density estimation

Arkadas Ozakin, Alexander G. Gray

On Invariance in Hierarchical Models

Jake Bouvrie, Lorenzo Rosasco, Tomaso Poggio

Structured output regression for detection with partial truncation

Andrea Vedaldi, Andrew Zisserman

On Stochastic and Worst-case Models for Investing

Elad Hazan, Satyen Kale

From PAC-Bayes Bounds to KL Regularization

Pascal Germain, Alexandre Lacasse, Mario Marchand, Sara Shanian, François Laviolette

Linear-time Algorithms for Pairwise Statistical Problems

Parikshit Ram, Dongryeol Lee, William March, Alexander G. Gray

Information-theoretic lower bounds on the oracle complexity of convex optimization

Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett, Pradeep K Ravikumar, Pradeep K. Ravikumar

Which graphical models are difficult to learn?

Andrea Montanari, Jose A. Pereira

Heavy-Tailed Symmetric Stochastic Neighbor Embedding

Zhirong Yang, Irwin King, Zenglin Xu, Erkki Oja

Filtering Abstract Senses From Image Search Results

Kate Saenko, Trevor Darrell

Matrix Completion from Power-Law Distributed Samples

Raghu Meka, Prateek Jain, Inderjit S Dhillon, Inderjit S. Dhillon

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process

Finale Doshi-velez, Shakir Mohamed, Zoubin Ghahramani, David A. Knowles

An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism

Douglas Eck, Yoshua Bengio, Aaron C. Courville

Modeling the spacing effect in sequential category learning

Hongjing Lu, Matthew Weiden, Alan L. Yuille

Sparse Estimation Using General Likelihoods and Non-Factorial Priors

David P. Wipf, Srikantan S. Nagarajan

Factor Modeling for Advertisement Targeting

Ye Chen, Michael Kapralov, John Canny, Dmitry Y. Pavlov

A Stochastic approximation method for inference in probabilistic graphical models

Peter Carbonetto, Matthew King, Firas Hamze

Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution

Cosmin Bejan, Matthew Titsworth, Andrew Hickl, Sanda Harabagiu

Streaming Pointwise Mutual Information

Benjamin V. Durme, Ashwin Lall

Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Jie Luo, Barbara Caputo, Vittorio Ferrari

Sensitivity analysis in HMMs with application to likelihood maximization

Pierre-arnaud Coquelin, Romain Deguest, Rémi Munos

Semi-Supervised Learning in Gigantic Image Collections

Rob Fergus, Yair Weiss, Antonio Torralba

Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition

Natasha Singh-miller, Michael Collins

Zero-shot Learning with Semantic Output Codes

Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell

Bilinear classifiers for visual recognition

Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes

Gaussian process regression with Student-t likelihood

Jarno Vanhatalo, Pasi Jylänki, Aki Vehtari

Potential-Based Agnostic Boosting

Varun Kanade, Adam Kalai

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data

Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu

Non-stationary continuous dynamic Bayesian networks

Marco Grzegorczyk, Dirk Husmeier

Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning

Anne Hsu, Thomas L. Griffiths

Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity

Andreas Bartels, Matthew Blaschko, Jacquelyn A. Shelton

Rethinking LDA: Why Priors Matter

Hanna M. Wallach, David M. Mimno, Andrew McCallum

Nonparametric Greedy Algorithms for the Sparse Learning Problem

Han Liu, Xi Chen

Directed Regression

Yi-hao Kao, Benjamin V. Roy, Xiang Yan

Fast subtree kernels on graphs

Nino Shervashidze, Karsten Borgwardt

Multi-Label Prediction via Sparse Infinite CCA

Piyush Rai, Hal Daume

Free energy score space

Alessandro Perina, Marco Cristani, Umberto Castellani, Vittorio Murino, Nebojsa Jojic

Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks

Stefan Klampfl, Wolfgang Maass

Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification

Amarnag Subramanya, Jeff A. Bilmes

Spatial Normalized Gamma Processes

Vinayak Rao, Yee W. Teh

Positive Semidefinite Metric Learning with Boosting

Chunhua Shen, Junae Kim, Lei Wang, Anton Hengel

Code-specific policy gradient rules for spiking neurons

Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner

Yoshua Bengio, James S. Bergstra

Neurometric function analysis of population codes

Philipp Berens, Sebastian Gerwinn, Alexander Ecker, Matthias Bethge

Learning models of object structure

Joseph Schlecht, Kobus Barnard

White Functionals for Anomaly Detection in Dynamical Systems

Marco Cuturi, Jean-philippe Vert, Alexandre D'aspremont

Compressed Least-Squares Regression

Odalric Maillard, Rémi Munos

DUOL: A Double Updating Approach for Online Learning

Peilin Zhao, Steven C. Hoi, Rong Jin

Monte Carlo Sampling for Regret Minimization in Extensive Games

Marc Lanctot, Kevin Waugh, Martin Zinkevich, Michael Bowling