NeurIPS 2010

292 papers

Online Classification with Specificity Constraints

Andrey Bernstein, Shie Mannor, Nahum Shimkin

Minimum Average Cost Clustering

Kiyohito Nagano, Yoshinobu Kawahara, Satoru Iwata

Tight Sample Complexity of Large-Margin Learning

Sivan Sabato, Nathan Srebro, Naftali Tishby

Sphere Embedding: An Application to Part-of-Speech Induction

Yariv Maron, Michael Lamar, Elie Bienenstock

Humans Learn Using Manifolds, Reluctantly

Tim Rogers, Chuck Kalish, Joseph Harrison, Xiaojin Zhu, Bryan R. Gibson

Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression

Ling Huang, Jinzhu Jia, Bin Yu, Byung-gon Chun, Petros Maniatis

Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach

Alessandro Bergamo, Lorenzo Torresani

Occlusion Detection and Motion Estimation with Convex Optimization

Alper Ayvaci, Michalis Raptis, Stefano Soatto

t-logistic regression

Nan Ding, S.v.n. Vishwanathan

Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings

Ziv Bar-joseph, Hai-son P. Le

Sidestepping Intractable Inference with Structured Ensemble Cascades

David Weiss, Benjamin Sapp, Ben Taskar

A novel family of non-parametric cumulative based divergences for point processes

Sohan Seth, Park Il, Austin Brockmeier, Mulugeta Semework, John Choi

Multivariate Dyadic Regression Trees for Sparse Learning Problems

Han Liu, Xi Chen

A Bayesian Approach to Concept Drift

Stephen Bach, Mark Maloof

Predictive Subspace Learning for Multi-view Data: a Large Margin Approach

Ning Chen, Jun Zhu, Eric P. Xing

Learning Networks of Stochastic Differential Equations

José Pereira, Morteza Ibrahimi, Andrea Montanari

A New Probabilistic Model for Rank Aggregation

Tao Qin, Xiubo Geng, Tie-yan Liu

Heavy-Tailed Process Priors for Selective Shrinkage

Fabian L. Wauthier, Michael I. Jordan

A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups

Sofia Mosci, Silvia Villa, Alessandro Verri, Lorenzo Rosasco

A biologically plausible network for the computation of orientation dominance

Kritika Muralidharan, Nuno Vasconcelos

Sample Complexity of Testing the Manifold Hypothesis

Hariharan Narayanan, Sanjoy Mitter

The Neural Costs of Optimal Control

Samuel Gershman, Robert Wilson

Spike timing-dependent plasticity as dynamic filter

Joscha Schmiedt, Christian Albers, Klaus Pawelzik

A Family of Penalty Functions for Structured Sparsity

Jean Morales, Charles A. Micchelli, Massimiliano Pontil

Bayesian Action-Graph Games

Albert X. Jiang, Kevin Leyton-brown

Penalized Principal Component Regression on Graphs for Analysis of Subnetworks

Ali Shojaie, George Michailidis

Probabilistic Multi-Task Feature Selection

Yu Zhang, Dit-Yan Yeung, Qian Xu

Graph-Valued Regression

Han Liu, Xi Chen, Larry Wasserman, John D. Lafferty

Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks

Dirk Husmeier, Frank Dondelinger, Sophie Lebre

Linear Complementarity for Regularized Policy Evaluation and Improvement

Jeffrey Johns, Christopher Painter-wakefield, Ronald Parr

Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez

Global Analytic Solution for Variational Bayesian Matrix Factorization

Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka

Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models

Anand Singh, Renaud Jolivet, Pierre Magistretti, Bruno Weber

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake

Stefan Harmeling, Hirsch Michael, Bernhard Schölkopf

Layer-wise analysis of deep networks with Gaussian kernels

Grégoire Montavon, Klaus-Robert Müller, Mikio L. Braun

Attractor Dynamics with Synaptic Depression

K. Wong, He Wang, Si Wu, Chi Fung

Fast global convergence rates of gradient methods for high-dimensional statistical recovery

Alekh Agarwal, Sahand Negahban, Martin J. Wainwright

Permutation Complexity Bound on Out-Sample Error

Malik Magdon-Ismail

SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system

Sylvain Chevallier, Hél\`ene Paugam-moisy, Michele Sebag

A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration

Yi-da Wu, Shi-jie Lin, Hsin Chen

Online Markov Decision Processes under Bandit Feedback

Gergely Neu, András Antos, András György, Csaba Szepesvári

A Bayesian Framework for Figure-Ground Interpretation

Vicky Froyen, Jacob Feldman, Manish Singh

Deterministic Single-Pass Algorithm for LDA

Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa

Random Conic Pursuit for Semidefinite Programming

Ariel Kleiner, Ali Rahimi, Michael I. Jordan

Energy Disaggregation via Discriminative Sparse Coding

J. Z. Kolter, Siddharth Batra, Andrew Y. Ng

Smoothness, Low Noise and Fast Rates

Nathan Srebro, Karthik Sridharan, Ambuj Tewari

Inference and communication in the game of Password

Yang Xu, Charles Kemp

Random Projections for k-means Clustering

Christos Boutsidis, Anastasios Zouzias, Petros Drineas

Online Learning for Latent Dirichlet Allocation

Matthew Hoffman, Francis R. Bach, David M. Blei

Spectral Regularization for Support Estimation

Ernesto D. Vito, Lorenzo Rosasco, Alessandro Toigo

Exact inference and learning for cumulative distribution functions on loopy graphs

Nebojsa Jojic, Chris Meek, Jim C. Huang

Movement extraction by detecting dynamics switches and repetitions

Silvia Chiappa, Jan R. Peters

Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch

Zeeshan Syed, John V. Guttag

Regularized estimation of image statistics by Score Matching

Diederik P. Kingma, Yann L. Cun

The Maximal Causes of Natural Scenes are Edge Filters

Jose Puertas, Joerg Bornschein, Jörg Lücke

Implicit Differentiation by Perturbation

Justin Domke

Efficient Minimization of Decomposable Submodular Functions

Peter Stobbe, Andreas Krause

Generating more realistic images using gated MRF's

Marc'aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton

Simultaneous Object Detection and Ranking with Weak Supervision

Matthew Blaschko, Andrea Vedaldi, Andrew Zisserman

Improvements to the Sequence Memoizer

Jan Gasthaus, Yee W. Teh

Fast Large-scale Mixture Modeling with Component-specific Data Partitions

Bo Thiesson, Chong Wang

Learning concept graphs from text with stick-breaking priors

America Chambers, Padhraic Smyth, Mark Steyvers

Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework

Hongbo Zhou, Qiang Cheng

Policy gradients in linearly-solvable MDPs

Emanuel Todorov

A rational decision making framework for inhibitory control

Pradeep Shenoy, Angela J. Yu, Rajesh P. Rao

An Alternative to Low-level-Sychrony-Based Methods for Speech Detection

Javier R. Movellan, Paul L. Ruvolo

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski, Hartwig Siebner, Lars K. Hansen

A POMDP Extension with Belief-dependent Rewards

Mauricio Araya, Olivier Buffet, Vincent Thomas, Françcois Charpillet

Worst-case bounds on the quality of max-product fixed-points

Meritxell Vinyals, Jes\'us Cerquides, Alessandro Farinelli, Juan A. Rodríguez-aguilar

Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm

Nathan Srebro, Ruslan Salakhutdinov

Learning to combine foveal glimpses with a third-order Boltzmann machine

Hugo Larochelle, Geoffrey E. Hinton

PAC-Bayesian Model Selection for Reinforcement Learning

Mahdi M. Fard, Joelle Pineau

Error Propagation for Approximate Policy and Value Iteration

Amir-massoud Farahmand, Csaba Szepesvári, Rémi Munos

Subgraph Detection Using Eigenvector L1 Norms

Benjamin Miller, Nadya Bliss, Patrick J. Wolfe

Scrambled Objects for Least-Squares Regression

Odalric Maillard, Rémi Munos

Improving Human Judgments by Decontaminating Sequential Dependencies

Michael Mozer, Harold Pashler, Matthew Wilder, Robert Lindsey, Matt Jones

Feature Set Embedding for Incomplete Data

David Grangier, Iain Melvin

Extensions of Generalized Binary Search to Group Identification and Exponential Costs

Gowtham Bellala, Suresh Bhavnani, Clayton Scott

A Reduction from Apprenticeship Learning to Classification

Umar Syed, Robert E. Schapire

Learning Bounds for Importance Weighting

Corinna Cortes, Yishay Mansour, Mehryar Mohri

Causal discovery in multiple models from different experiments

Tom Claassen, Tom Heskes

Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs

Dávid Pál, Barnabás Póczos, Csaba Szepesvári

Gated Softmax Classification

Roland Memisevic, Christopher Zach, Marc Pollefeys, Geoffrey E. Hinton

Semi-Supervised Learning with Adversarially Missing Label Information

Umar Syed, Ben Taskar

Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets

Paolo Viappiani, Craig Boutilier

Active Learning by Querying Informative and Representative Examples

Sheng-jun Huang, Rong Jin, Zhi-Hua Zhou

Network Flow Algorithms for Structured Sparsity

Julien Mairal, Rodolphe Jenatton, Francis R. Bach, Guillaume R. Obozinski

Learning Multiple Tasks with a Sparse Matrix-Normal Penalty

Yi Zhang, Jeff G. Schneider

Worst-Case Linear Discriminant Analysis

Yu Zhang, Dit-Yan Yeung

Universal Kernels on Non-Standard Input Spaces

Andreas Christmann, Ingo Steinwart

Efficient Optimization for Discriminative Latent Class Models

Armand Joulin, Jean Ponce, Francis R. Bach

Slice sampling covariance hyperparameters of latent Gaussian models

Iain Murray, Ryan P. Adams

Optimal Web-Scale Tiering as a Flow Problem

Gilbert Leung, Novi Quadrianto, Kostas Tsioutsiouliklis, Alex J. Smola

Structured sparsity-inducing norms through submodular functions

Francis R. Bach

Co-regularization Based Semi-supervised Domain Adaptation

Abhishek Kumar, Avishek Saha, Hal Daume

Bootstrapping Apprenticeship Learning

Abdeslam Boularias, Brahim Chaib-draa

Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning

Prateek Jain, Sudheendra Vijayanarasimhan, Kristen Grauman

A Theory of Multiclass Boosting

Indraneel Mukherjee, Robert E. Schapire

Gaussian Process Preference Elicitation

Shengbo Guo, Scott Sanner, Edwin V. Bonilla

Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning

Matthias Broecheler, Lise Getoor