NeurIPS 2006

204 papers

Relational Learning with Gaussian Processes

Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. S. Keerthi

Denoising and Dimension Reduction in Feature Space

Mikio L. Braun, Klaus-Robert Müller, Joachim M Buhmann, Joachim M. Buhmann

Boosting Structured Prediction for Imitation Learning

J. A. Bagnell, Joel Chestnutt, David M. Bradley, Nathan D. Ratliff

Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms

Xinhua Zhang, Wee S. Lee

MLLE: Modified Locally Linear Embedding Using Multiple Weights

Zhenyue Zhang, Jing Wang

Large Scale Hidden Semi-Markov SVMs

Gunnar Rätsch, Sören Sonnenburg

Sample Complexity of Policy Search with Known Dynamics

Peter L. Bartlett, Ambuj Tewari

Learnability and the doubling dimension

Yi Li, Philip M. Long

TrueSkill™: A Bayesian Skill Rating System

Ralf Herbrich, Tom Minka, Thore Graepel

Modelling transcriptional regulation using Gaussian Processes

Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray

Distributed Inference in Dynamical Systems

Stanislav Funiak, Carlos Guestrin, Rahul Sukthankar, Mark A. Paskin

A PAC-Bayes Risk Bound for General Loss Functions

Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand

No-regret Algorithms for Online Convex Programs

Geoffrey J. Gordon

Large Margin Hidden Markov Models for Automatic Speech Recognition

Fei Sha, Lawrence K. Saul

Unsupervised Regression with Applications to Nonlinear System Identification

Ali Rahimi, Ben Recht

Conditional mean field

Peter Carbonetto, Nando D. Freitas

Nonlinear physically-based models for decoding motor-cortical population activity

Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black

Emergence of conjunctive visual features by quadratic independent component analysis

J.t. Lindgren, Aapo Hyvärinen

Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model

Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers

A Kernel Method for the Two-Sample-Problem

Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alex J. Smola

On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts

Hariharan Narayanan, Mikhail Belkin, Partha Niyogi

Scalable Discriminative Learning for Natural Language Parsing and Translation

Joseph Turian, Benjamin Wellington, I. D. Melamed

Max-margin classification of incomplete data

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

Multi-dynamic Bayesian Networks

Karim Filali, Jeff A. Bilmes

Fast Computation of Graph Kernels

Karsten Borgwardt, Nicol N. Schraudolph, S.v.n. Vishwanathan

Learning Dense 3D Correspondence

Florian Steinke, Volker Blanz, Bernhard Schölkopf

Learning with Hypergraphs: Clustering, Classification, and Embedding

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf

Kernels on Structured Objects Through Nested Histograms

Marco Cuturi, Kenji Fukumizu

Large Margin Component Analysis

Lorenzo Torresani, Kuang-chih Lee

Clustering appearance and shape by learning jigsaws

Anitha Kannan, John Winn, Carsten Rother

An Oracle Inequality for Clipped Regularized Risk Minimizers

Ingo Steinwart, Don Hush, Clint Scovel

Learning on Graph with Laplacian Regularization

Rie K. Ando, Tong Zhang

Linearly-solvable Markov decision problems

Emanuel Todorov

Learning Motion Style Synthesis from Perceptual Observations

Lorenzo Torresani, Peggy Hackney, Christoph Bregler

Fast Discriminative Visual Codebooks using Randomized Clustering Forests

Frank Moosmann, Bill Triggs, Frederic Jurie

Balanced Graph Matching

Timothee Cour, Praveen Srinivasan, Jianbo Shi

Efficient Methods for Privacy Preserving Face Detection

Shai Avidan, Moshe Butman

Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization

Rey Ramírez, Jason Palmer, Scott Makeig, David P. Wipf, Bhaskar D Rao

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models

S. S. Keerthi, Vikas Sindhwani, Olivier Chapelle

Prediction on a Graph with a Perceptron

Mark Herbster, Massimiliano Pontil

An Information Theoretic Framework for Eukaryotic Gradient Sensing

Joseph M. Kimmel, Richard M. Salter, Peter J. Thomas

Similarity by Composition

Oren Boiman, Michal Irani

Sparse Representation for Signal Classification

Ke Huang, Selin Aviyente

Simplifying Mixture Models through Function Approximation

Kai Zhang, James T. Kwok

Learning Structural Equation Models for fMRI

Enrico Simonotto, Heather Whalley, Stephen Lawrie, Lawrence Murray, David Mcgonigle

Speakers optimize information density through syntactic reduction

T. F. Jaeger, Roger P. Levy

Uncertainty, phase and oscillatory hippocampal recall

Máté Lengyel, Peter Dayan

Fast Iterative Kernel PCA

Nicol N. Schraudolph, Simon Günter, S.v.n. Vishwanathan

Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning

Peter Auer, Ronald Ortner

Inferring Network Structure from Co-Occurrences

Michael G. Rabbat, Mário Figueiredo, Robert Nowak

Clustering Under Prior Knowledge with Application to Image Segmentation

Dong S. Cheng, Vittorio Murino, Mário Figueiredo

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning

Hamed Valizadegan, Rong Jin

Fundamental Limitations of Spectral Clustering

Boaz Nadler, Meirav Galun

An Approach to Bounded Rationality

Eli Ben-sasson, Ehud Kalai, Adam Kalai

A Theory of Retinal Population Coding

Eizaburo Doi, Michael S. Lewicki

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons

Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein

A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems

David Barber, Bertrand Mesot

Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning

Gediminas Lukšys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods

Matthias Seeger

AdaBoost is Consistent

Peter L. Bartlett, Mikhail Traskin

A Complexity-Distortion Approach to Joint Pattern Alignment

Andrea Vedaldi, Stefano Soatto

Gaussian and Wishart Hyperkernels

Risi Kondor, Tony Jebara

Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation

Gavin C. Cawley, Nicola L. Talbot, Mark Girolami

Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation

Jason M. Samonds, Brian R. Potetz, Tai S. Lee

Analysis of Representations for Domain Adaptation

Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira

Learning to Rank with Nonsmooth Cost Functions

Christopher J. Burges, Robert Ragno, Quoc V Le, Quoc V. Le

Optimal Single-Class Classification Strategies

Ran El-Yaniv, Mordechai Nisenson

Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games

Chris Murray, Geoffrey J. Gordon

Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data

Ping Li, Kenneth W. Church, Trevor J. Hastie

PG-means: learning the number of clusters in data

Yu Feng, Greg Hamerly

implicit Online Learning with Kernels

Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli, S.v.n. Vishwanathan

Mixture Regression for Covariate Shift

Masashi Sugiyama, Amos J. Storkey

Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions

Philip M. Long, Rocco Servedio

Efficient Structure Learning of Markov Networks using L_1-Regularization

Su-in Lee, Varun Ganapathi, Daphne Koller

Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension

Manfred K. Warmuth, Dima Kuzmin

Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees

Konrad Rieck, Pavel Laskov, Sören Sonnenburg

A Nonparametric Approach to Bottom-Up Visual Saliency

Wolf Kienzle, Felix A. Wichmann, Matthias O. Franz, Bernhard Schölkopf

Correcting Sample Selection Bias by Unlabeled Data

Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, Alex J. Smola

Learning to parse images of articulated bodies

Deva Ramanan

Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds

Benjamin I. Rubinstein, Peter L. Bartlett, J. H. Rubinstein

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields

Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner

Manifold Denoising

Matthias Hein, Markus Maier

Support Vector Machines on a Budget

Ofer Dekel, Yoram Singer

Chained Boosting

Christian R. Shelton, Wesley Huie, Kin F. Kan

Image Retrieval and Classification Using Local Distance Functions

Andrea Frome, Yoram Singer, Jitendra Malik

Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype

Tobias Sing, Niko Beerenwinkel

A Humanlike Predictor of Facial Attractiveness

Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-or, Eytan Ruppin

Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing

Yuanhao Chen, Long Zhu, Alan L. Yuille

The Neurodynamics of Belief Propagation on Binary Markov Random Fields

Thomas Ott, Ruedi Stoop

Recursive ICA

Honghao Shan, Lingyun Zhang, Garrison W. Cottrell

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments

Michael I. Mandel, Daniel P. Ellis, Tony Jebara

Parameter Expanded Variational Bayesian Methods

Tommi S. Jaakkola, Yuan Qi

An Application of Reinforcement Learning to Aerobatic Helicopter Flight

Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng

Context Effects in Category Learning: An Investigation of Four Probabilistic Models

Michael Mozer, Michael Shettel, Michael P. Holmes

Approximate inference using planar graph decomposition

Amir Globerson, Tommi S. Jaakkola

A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems

Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida

Causal inference in sensorimotor integration

Konrad P. Körding, Joshua B. Tenenbaum

Learning to be Bayesian without Supervision

Martin Raphan, Eero P. Simoncelli

Analysis of Contour Motions

Ce Liu, William T. Freeman, Edward H. Adelson

Multi-Instance Multi-Label Learning with Application to Scene Classification

Zhi-Li Zhang, Min-ling Zhang