NeurIPS 2007

217 papers

Multiple-Instance Pruning For Learning Efficient Cascade Detectors

Cha Zhang, Paul A. Viola

Non-parametric Modeling of Partially Ranked Data

Guy Lebanon, Yi Mao

The rat as particle filter

Aaron C. Courville, Nathaniel D. Daw

Consistent Minimization of Clustering Objective Functions

Ulrike V. Luxburg, Stefanie Jegelka, Michael Kaufmann, Sébastien Bubeck

Regularized Boost for Semi-Supervised Learning

Ke Chen, Shihai Wang

Infinite State Bayes-Nets for Structured Domains

Max Welling, Ian Porteous, Evgeniy Bart

COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking

Markus Weimer, Alexandros Karatzoglou, Alex J. Smola, Quoc V Le, Quoc V. Le

Learning Horizontal Connections in a Sparse Coding Model of Natural Images

Pierre Garrigues, Bruno A. Olshausen

Linear programming analysis of loopy belief propagation for weighted matching

Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky

Hierarchical Penalization

Marie Szafranski, Yves Grandvalet, Pierre Morizet-mahoudeaux

Experience-Guided Search: A Theory of Attentional Control

David Baldwin, Michael Mozer

Progressive mixture rules are deviation suboptimal

Jean-yves Audibert

Collapsed Variational Inference for HDP

Yee W. Teh, Kenichi Kurihara, Max Welling

Learning Visual Attributes

Vittorio Ferrari, Andrew Zisserman

Spatial Latent Dirichlet Allocation

Xiaogang Wang, Eric Grimson

Selecting Observations against Adversarial Objectives

Andreas Krause, Brendan Mcmahan, Carlos Guestrin, Anupam Gupta

Feature Selection Methods for Improving Protein Structure Prediction with Rosetta

Ben Blum, David Baker, Michael I. Jordan, Philip Bradley, Rhiju Das

Catching Change-points with Lasso

Céline Levy-leduc, Zaïd Harchaoui

Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria

Elad Hazan, Satyen Kale

A neural network implementing optimal state estimation based on dynamic spike train decoding

Omer Bobrowski, Ron Meir, Shy Shoham, Yonina Eldar

Object Recognition by Scene Alignment

Bryan Russell, Antonio Torralba, Ce Liu, Rob Fergus, William T. Freeman

Parallelizing Support Vector Machines on Distributed Computers

Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu

A Bayesian Framework for Cross-Situational Word-Learning

Noah Goodman, Joshua B. Tenenbaum, Michael J. Black

Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination

Yiu M. Lam, Bertram E. Shi

Agreement-Based Learning

Percy Liang, Dan Klein, Michael I. Jordan

Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression

Sennay Ghebreab, Arnold Smeulders, Pieter Adriaans

Blind channel identification for speech dereverberation using l1-norm sparse learning

Yuanqing Lin, Jingdong Chen, Youngmoo Kim, Daniel D. Lee

Fitted Q-iteration in continuous action-space MDPs

András Antos, Csaba Szepesvári, Rémi Munos

Efficient Inference for Distributions on Permutations

Jonathan Huang, Carlos Guestrin, Leonidas Guibas

Density Estimation under Independent Similarly Distributed Sampling Assumptions

Tony Jebara, Yingbo Song, Kapil Thadani

Probabilistic Matrix Factorization

Andriy Mnih, Ruslan Salakhutdinov

Discriminative Keyword Selection Using Support Vector Machines

Fred Richardson, William M. Campbell

A Kernel Statistical Test of Independence

Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf

Supervised Topic Models

Jon D. Mcauliffe, David M. Blei

Bayesian Co-Training

Shipeng Yu, Balaji Krishnapuram, Harald Steck, R. B. Rao, Rómer Rosales

Privacy-Preserving Belief Propagation and Sampling

Michael Kearns, Jinsong Tan, Jennifer Wortman

Near-Maximum Entropy Models for Binary Neural Representations of Natural Images

Matthias Bethge, Philipp Berens

Gaussian Process Models for Link Analysis and Transfer Learning

Kai Yu, Wei Chu

Boosting Algorithms for Maximizing the Soft Margin

Gunnar Rätsch, Manfred K. Warmuth, Karen A. Glocer

What makes some POMDP problems easy to approximate?

Wee S. Lee, Nan Rong, David Hsu

Comparing Bayesian models for multisensory cue combination without mandatory integration

Ulrik Beierholm, Ladan Shams, Wei J. Ma, Konrad Koerding

Discriminative Batch Mode Active Learning

Yuhong Guo, Dale Schuurmans

Measuring Neural Synchrony by Message Passing

Justin Dauwels, François Vialatte, Tomasz Rutkowski, Andrzej S. Cichocki

Scene Segmentation with CRFs Learned from Partially Labeled Images

Bill Triggs, Jakob J. Verbeek

A Game-Theoretic Approach to Apprenticeship Learning

Umar Syed, Robert E. Schapire

Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning

Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey Kephart, David Levine

A Risk Minimization Principle for a Class of Parzen Estimators

Kristiaan Pelckmans, Johan Suykens, Bart D. Moor

Receding Horizon Differential Dynamic Programming

Yuval Tassa, Tom Erez, William D. Smart

Sparse Feature Learning for Deep Belief Networks

Marc'aurelio Ranzato, Y-lan Boureau, Yann L. Cun

Boosting the Area under the ROC Curve

Phil Long, Rocco Servedio

Message Passing for Max-weight Independent Set

Sujay Sanghavi, Devavrat Shah, Alan S. Willsky

Efficient Convex Relaxation for Transductive Support Vector Machine

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

Learning to classify complex patterns using a VLSI network of spiking neurons

Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi

Automatic Generation of Social Tags for Music Recommendation

Douglas Eck, Paul Lamere, Thierry Bertin-mahieux, Stephen Green

A probabilistic model for generating realistic lip movements from speech

Gwenn Englebienne, Tim Cootes, Magnus Rattray

Learning with Transformation Invariant Kernels

Christian Walder, Olivier Chapelle

Support Vector Machine Classification with Indefinite Kernels

Ronny Luss, Alexandre D'aspremont

Iterative Non-linear Dimensionality Reduction with Manifold Sculpting

Michael Gashler, Dan Ventura, Tony Martinez

The Price of Bandit Information for Online Optimization

Varsha Dani, Sham M. Kakade, Thomas P. Hayes

Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation

Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V. Buenau, Motoaki Kawanabe

A Randomized Algorithm for Large Scale Support Vector Learning

Krishnan Kumar, Chiru Bhattacharya, Ramesh Hariharan

McRank: Learning to Rank Using Multiple Classification and Gradient Boosting

Ping Li, Qiang Wu, Christopher J. Burges

Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations

M. M. Mahmud, Sylvian Ray

Online Linear Regression and Its Application to Model-Based Reinforcement Learning

Alexander L. Strehl, Michael L. Littman

Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms

Dominik Endres, Mike Oram, Johannes Schindelin, Peter Foldiak

Active Preference Learning with Discrete Choice Data

Brochu Eric, Nando D. Freitas, Abhijeet Ghosh

Retrieved context and the discovery of semantic structure

Vinayak Rao, Marc Howard

The Infinite Markov Model

Daichi Mochihashi, Eiichiro Sumita

Learning and using relational theories

Charles Kemp, Noah Goodman, Joshua B. Tenenbaum

Fast Variational Inference for Large-scale Internet Diagnosis

Emre Kiciman, David Maltz, John C. Platt

On higher-order perceptron algorithms

Claudio Gentile, Fabio Vitale, Cristian Brotto

The Value of Labeled and Unlabeled Examples when the Model is Imperfect

Kaushik Sinha, Mikhail Belkin

One-Pass Boosting

Zafer Barutcuoglu, Phil Long, Rocco Servedio

Exponential Family Predictive Representations of State

David Wingate, Satinder S. Baveja

An Analysis of Inference with the Universum

Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz, Bernhard Schölkopf

Heterogeneous Component Analysis

Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii

Discriminative K-means for Clustering

Jieping Ye, Zheng Zhao, Mingrui Wu

Optimal models of sound localization by barn owls

Brian J. Fischer

Mining Internet-Scale Software Repositories

Erik Linstead, Paul Rigor, Sushil Bajracharya, Cristina Lopes, Pierre F. Baldi

Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons

Emre Neftci, Elisabetta Chicca, Giacomo Indiveri, Jean-jeacques Slotine, Rodney J. Douglas

Semi-Supervised Multitask Learning

Qiuhua Liu, Xuejun Liao, Lawrence Carin

Multiple-Instance Active Learning

Burr Settles, Mark Craven, Soumya Ray

Combined discriminative and generative articulated pose and non-rigid shape estimation

Leonid Sigal, Alexandru Balan, Michael J. Black

Learning Monotonic Transformations for Classification

Andrew Howard, Tony Jebara

Learning the structure of manifolds using random projections

Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma

Topmoumoute Online Natural Gradient Algorithm

Nicolas L. Roux, Pierre-antoine Manzagol, Yoshua Bengio

TrueSkill Through Time: Revisiting the History of Chess

Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel

Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs

Ambuj Tewari, Peter L. Bartlett

HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation

Bing Zhao, Eric P. Xing

Discriminative Log-Linear Grammars with Latent Variables

Slav Petrov, Dan Klein

Sequential Hypothesis Testing under Stochastic Deadlines

Peter Frazier, Angela J. Yu

A New View of Automatic Relevance Determination

David P. Wipf, Srikantan S. Nagarajan

Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity

Dejan Pecevski, Wolfgang Maass, Robert A. Legenstein

CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation

Luis E. Ortiz

A Spectral Regularization Framework for Multi-Task Structure Learning

Andreas Argyriou, Massimiliano Pontil, Yiming Ying, Charles A. Micchelli

Cooled and Relaxed Survey Propagation for MRFs

Hai L. Chieu, Wee S. Lee, Yee W. Teh

The Generalized FITC Approximation

Andrew Naish-guzman, Sean Holden

Modeling image patches with a directed hierarchy of Markov random fields

Simon Osindero, Geoffrey E. Hinton

Hidden Common Cause Relations in Relational Learning

Ricardo Silva, Wei Chu, Zoubin Ghahramani

Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons

Lars Buesing, Wolfgang Maass