NeurIPS 2006

204 papers

Differential Entropic Clustering of Multivariate Gaussians

Jason V. Davis, Inderjit S Dhillon, Inderjit S. Dhillon

Branch and Bound for Semi-Supervised Support Vector Machines

Olivier Chapelle, Vikas Sindhwani, S. S. Keerthi

Using Combinatorial Optimization within Max-Product Belief Propagation

Daniel Tarlow, Gal Elidan, Daphne Koller, John C. Duchi

Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models

Alexander T. Ihler, Padhraic Smyth

Efficient Learning of Sparse Representations with an Energy-Based Model

Marc'aurelio Ranzato, Christopher Poultney, Sumit Chopra, Yann L. Cun

High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression

Martin J. Wainwright, John D. Lafferty, Pradeep K Ravikumar, Pradeep K. Ravikumar

Real-time adaptive information-theoretic optimization of neurophysiology experiments

Jeremy Lewi, Robert Butera, Liam Paninski

A selective attention multi--chip system with dynamic synapses and spiking neurons

Chiara Bartolozzi, Giacomo Indiveri

Multiple Instance Learning for Computer Aided Diagnosis

Murat Dundar, Balaji Krishnapuram, R. B. Rao, Glenn M. Fung

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions

Christian Walder, Olivier Chapelle, Bernhard Schölkopf

Natural Actor-Critic for Road Traffic Optimisation

Silvia Richter, Douglas Aberdeen, Jin Yu

Map-Reduce for Machine Learning on Multicore

Cheng-tao Chu, Sang K. Kim, Yi-an Lin, Yuanyuan Yu, Gary Bradski

Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space

Wenye Li, Kin-hong Lee, Kwong-sak Leung

PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier

Alexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier

Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons

Elisabetta Chicca, Giacomo Indiveri, Rodney J. Douglas

Nonnegative Sparse PCA

Ron Zass, Amnon Shashua

Inducing Metric Violations in Human Similarity Judgements

Julian Laub, Klaus-Robert Müller, Felix A. Wichmann, Jakob H. Macke

A recipe for optimizing a time-histogram

Hideaki Shimazaki, Shigeru Shinomoto

Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces

Moritz Grosse-wentrup, Klaus Gramann, Martin Buss

Stochastic Relational Models for Discriminative Link Prediction

Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu

Data Integration for Classification Problems Employing Gaussian Process Priors

Mark Girolami, Mingjun Zhong

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets

Jerónimo Arenas-garcía, Kaare B. Petersen, Lars K. Hansen

iLSTD: Eligibility Traces and Convergence Analysis

Alborz Geramifard, Michael Bowling, Martin Zinkevich, Richard S. Sutton

A Small World Threshold for Economic Network Formation

Eyal Even-dar, Michael Kearns

Single Channel Speech Separation Using Factorial Dynamics

John R. Hershey, Trausti Kristjansson, Steven Rennie, Peder A. Olsen

Learning annotated hierarchies from relational data

Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka, Joshua B. Tenenbaum

Comparative Gene Prediction using Conditional Random Fields

Jade P. Vinson, David Decaprio, Matthew D. Pearson, Stacey Luoma, James E. Galagan

Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis

Amit Gore, Shantanu Chakrabartty

On Transductive Regression

Corinna Cortes, Mehryar Mohri

Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models

Mark Johnson, Thomas L. Griffiths, Sharon Goldwater

Automated Hierarchy Discovery for Planning in Partially Observable Environments

Laurent Charlin, Pascal Poupart, Romy Shioda

A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo

Oliver Williams

Temporal dynamics of information content carried by neurons in the primary visual cortex

Danko Nikolić, Stefan Haeusler, Wolf Singer, Wolfgang Maass

Optimal Change-Detection and Spiking Neurons

Angela J. Yu

Greedy Layer-Wise Training of Deep Networks

Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle

Part-based Probabilistic Point Matching using Equivalence Constraints

Graham Mcneill, Sethu Vijayakumar

Handling Advertisements of Unknown Quality in Search Advertising

Sandeep Pandey, Christopher Olston

Bayesian Policy Gradient Algorithms

Mohammad Ghavamzadeh, Yaakov Engel

Convergence of Laplacian Eigenmaps

Mikhail Belkin, Partha Niyogi

Stability of K-Means Clustering

Alexander Rakhlin, Andrea Caponnetto

Dirichlet-Enhanced Spam Filtering based on Biased Samples

Steffen Bickel, Tobias Scheffer

Subordinate class recognition using relational object models

Aharon B. Hillel, Daphna Weinshall

Dynamic Foreground/Background Extraction from Images and Videos using Random Patches

Le Lu, Gregory D. Hager

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation

Yee W. Teh, David Newman, Max Welling

Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds

Gloria Haro, Gregory Randall, Guillermo Sapiro

A Scalable Machine Learning Approach to Go

Lin Wu, Pierre F. Baldi

Doubly Stochastic Normalization for Spectral Clustering

Ron Zass, Amnon Shashua

Graph-Based Visual Saliency

Jonathan Harel, Christof Koch, Pietro Perona

A Bayesian Approach to Diffusion Models of Decision-Making and Response Time

Michael D. Lee, Ian G. Fuss, Daniel J. Navarro

Attentional Processing on a Spike-Based VLSI Neural Network

Yingxue Wang, Rodney J. Douglas, Shih-Chii Liu

A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data

Johanna M. Zumer, Hagai T. Attias, Kensuke Sekihara, Srikantan S. Nagarajan

Information Bottleneck for Non Co-Occurrence Data

Yevgeny Seldin, Noam Slonim, Naftali Tishby

Recursive Attribute Factoring

David Cohn, Deepak Verma, Karl Pfleger

Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints

Carla P. Gomes, Ashish Sabharwal, Bart Selman

Statistical Modeling of Images with Fields of Gaussian Scale Mixtures

Siwei Lyu, Eero P. Simoncelli

Tighter PAC-Bayes Bounds

Amiran Ambroladze, Emilio Parrado-hernández, John S. Shawe-taylor

Active learning for misspecified generalized linear models

Francis R. Bach

Learning Nonparametric Models for Probabilistic Imitation

David B. Grimes, Daniel R. Rashid, Rajesh P. Rao

Non-rigid point set registration: Coherent Point Drift

Andriy Myronenko, Xubo Song, Miguel Á. Carreira-Perpiñán

Large-Scale Sparsified Manifold Regularization

Ivor W. Tsang, James T. Kwok

Particle Filtering for Nonparametric Bayesian Matrix Factorization

Frank Wood, Thomas L. Griffiths

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks

Alexis Battle, Gal Chechik, Daphne Koller

A Local Learning Approach for Clustering

Mingrui Wu, Bernhard Schölkopf

Logistic Regression for Single Trial EEG Classification

Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller

Isotonic Conditional Random Fields and Local Sentiment Flow

Yi Mao, Guy Lebanon

Bayesian Model Scoring in Markov Random Fields

Sridevi Parise, Max Welling

Hierarchical Dirichlet Processes with Random Effects

Seyoung Kim, Padhraic Smyth

A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments

Daniel J. Navarro, Thomas L. Griffiths

Temporal Coding using the Response Properties of Spiking Neurons

Thomas Voegtlin

Approximate Correspondences in High Dimensions

Kristen Grauman, Trevor Darrell

Efficient sparse coding algorithms

Honglak Lee, Alexis Battle, Rajat Raina, Andrew Y. Ng

Online Clustering of Moving Hyperplanes

René Vidal

Accelerated Variational Dirichlet Process Mixtures

Kenichi Kurihara, Max Welling, Nikos Vlassis

Blind Motion Deblurring Using Image Statistics

Anat Levin

Aggregating Classification Accuracy across Time: Application to Single Trial EEG

Steven Lemm, Christin Schäfer, Gabriel Curio

Theory and Dynamics of Perceptual Bistability

Paul R. Schrater, Rashmi Sundareswara

Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach

Matthias Krauledat, Michael Schröder, Benjamin Blankertz, Klaus-Robert Müller

Modeling Dyadic Data with Binary Latent Factors

Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis

Training Conditional Random Fields for Maximum Labelwise Accuracy

Samuel S. Gross, Olga Russakovsky, Chuong B. Do, Serafim Batzoglou

Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure

Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin, Sean Cutler

Robotic Grasping of Novel Objects

Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y. Ng

In-Network PCA and Anomaly Detection

Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael I. Jordan, Anthony Joseph

Towards a general independent subspace analysis

Fabian J. Theis

Convex Repeated Games and Fenchel Duality

Shai Shalev-shwartz, Yoram Singer

Online Classification for Complex Problems Using Simultaneous Projections

Yonatan Amit, Shai Shalev-shwartz, Yoram Singer

Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space

Kyung-ah Sohn, Eric P. Xing

Detecting Humans via Their Pose

Alessandro Bissacco, Ming-Hsuan Yang, Stefano Soatto

Combining causal and similarity-based reasoning

Charles Kemp, Patrick Shafto, Allison Berke, Joshua B. Tenenbaum

The Robustness-Performance Tradeoff in Markov Decision Processes

Huan Xu, Shie Mannor

Bayesian Ensemble Learning

Hugh A. Chipman, Edward I. George, Robert E. Mcculloch

Geometric entropy minimization (GEM) for anomaly detection and localization

Alfred O. Hero

Bayesian Image Super-resolution, Continued

Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman

Modeling Human Motion Using Binary Latent Variables

Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis

Learning from Multiple Sources

Koby Crammer, Michael Kearns, Jennifer Wortman

Multiple timescales and uncertainty in motor adaptation

Konrad P. Körding, Joshua B. Tenenbaum, Reza Shadmehr

Blind source separation for over-determined delayed mixtures

Lars Omlor, Martin Giese

Predicting spike times from subthreshold dynamics of a neuron

Ryota Kobayashi, Shigeru Shinomoto

Multi-Task Feature Learning

Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil

Graph Laplacian Regularization for Large-Scale Semidefinite Programming

Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models

David Barber, Silvia Chiappa