Book

Ordinal Regression by Extended Binary Classification Ling Li, Hsuan-tien Lin

Learning to Traverse Image Manifolds Piotr Dollár, Vincent Rabaud, Serge Belongie

Game Theoretic Algorithms for Protein-DNA binding Luis Pérez-breva, Luis E. Ortiz, Chen-hsiang Yeang, Tommi Jaakkola

Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm Robert Jenssen, Torbjørn Eltoft, Mark Girolami, Deniz Erdogmus

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models David Barber, Silvia Chiappa

Graph Laplacian Regularization for Large-Scale Semidefinite Programming Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence Saul

Multi-Task Feature Learning Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil

Predicting spike times from subthreshold dynamics of a neuron Ryota Kobayashi, Shigeru Shinomoto

Blind source separation for over-determined delayed mixtures Lars Omlor, Martin Giese

Multiple timescales and uncertainty in motor adaptation Konrad Körding, Joshua Tenenbaum, Reza Shadmehr

Learning from Multiple Sources Koby Crammer, Michael Kearns, Jennifer Wortman

Modeling Human Motion Using Binary Latent Variables Graham W. Taylor, Geoffrey E. Hinton, Sam Roweis

Bayesian Image Super-resolution, Continued Lyndsey Pickup, David Capel, Stephen J. Roberts, Andrew Zisserman

Geometric entropy minimization (GEM) for anomaly detection and localization Alfred Hero

Bayesian Ensemble Learning Hugh Chipman, Edward George, Robert Mcculloch

The Robustness-Performance Tradeoff in Markov Decision Processes Huan Xu, Shie Mannor

Combining causal and similarity-based reasoning Charles Kemp, Patrick Shafto, Allison Berke, Joshua Tenenbaum

Detecting Humans via Their Pose Alessandro Bissacco, Ming-Hsuan Yang, Stefano Soatto

Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space Kyung-ah Sohn, Eric Xing

Online Classification for Complex Problems Using Simultaneous Projections Yonatan Amit, Shai Shalev-shwartz, Yoram Singer

Convex Repeated Games and Fenchel Duality Shai Shalev-shwartz, Yoram Singer

Towards a general independent subspace analysis Fabian Theis

In-Network PCA and Anomaly Detection Ling Huang, XuanLong Nguyen, Minos Garofalakis, Michael Jordan, Anthony Joseph, Nina Taft

Robotic Grasping of Novel Objects Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Ng

Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure Jennifer Listgarten, Radford Neal, Sam Roweis, Rachel Puckrin, Sean Cutler

Training Conditional Random Fields for Maximum Labelwise Accuracy Samuel Gross, Olga Russakovsky, Chuong B., Serafim Batzoglou

Modeling Dyadic Data with Binary Latent Factors Edward Meeds, Zoubin Ghahramani, Radford Neal, Sam Roweis

Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach Matthias Krauledat, Michael Schröder, Benjamin Blankertz, Klaus-Robert Müller

Theory and Dynamics of Perceptual Bistability Paul R. Schrater, Rashmi Sundareswara

Aggregating Classification Accuracy across Time: Application to Single Trial EEG Steven Lemm, Christin Schäfer, Gabriel Curio

Blind Motion Deblurring Using Image Statistics Anat Levin

Accelerated Variational Dirichlet Process Mixtures Kenichi Kurihara, Max Welling, Nikos Vlassis

Online Clustering of Moving Hyperplanes René Vidal

Efficient sparse coding algorithms Honglak Lee, Alexis Battle, Rajat Raina, Andrew Ng

Approximate Correspondences in High Dimensions Kristen Grauman, Trevor Darrell

Temporal Coding using the Response Properties of Spiking Neurons Thomas Voegtlin

A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments Daniel Navarro, Thomas Griffiths

Hierarchical Dirichlet Processes with Random Effects Seyoung Kim, Padhraic Smyth

Bayesian Model Scoring in Markov Random Fields Sridevi Parise, Max Welling

Isotonic Conditional Random Fields and Local Sentiment Flow Yi Mao, Guy Lebanon

Logistic Regression for Single Trial EEG Classification Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller

A Local Learning Approach for Clustering Mingrui Wu, Bernhard Schölkopf

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks Alexis Battle, Gal Chechik, Daphne Koller

Particle Filtering for Nonparametric Bayesian Matrix Factorization Frank Wood, Thomas Griffiths

Large-Scale Sparsified Manifold Regularization Ivor Tsang, James Kwok

Non-rigid point set registration: Coherent Point Drift Andriy Myronenko, Xubo Song, Miguel Carreira-Perpiñán

Learning Nonparametric Models for Probabilistic Imitation David Grimes, Daniel Rashid, Rajesh PN Rao

Active learning for misspecified generalized linear models Francis Bach

Tighter PAC-Bayes Bounds Amiran Ambroladze, Emilio Parrado-hernández, John Shawe-taylor

Statistical Modeling of Images with Fields of Gaussian Scale Mixtures Siwei Lyu, Eero Simoncelli

Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints Carla P. Gomes, Ashish Sabharwal, Bart Selman

Recursive Attribute Factoring David Cohn, Deepak Verma, Karl Pfleger

Information Bottleneck for Non Co-Occurrence Data Yevgeny Seldin, Noam Slonim, Naftali Tishby

A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data Johanna Zumer, Hagai Attias, Kensuke Sekihara, Srikantan Nagarajan

Attentional Processing on a Spike-Based VLSI Neural Network Yingxue Wang, Rodney Douglas, Shih-Chii Liu

A Bayesian Approach to Diffusion Models of Decision-Making and Response Time Michael Lee, Ian Fuss, Daniel Navarro

Graph-Based Visual Saliency Jonathan Harel, Christof Koch, Pietro Perona

Doubly Stochastic Normalization for Spectral Clustering Ron Zass, Amnon Shashua

A Scalable Machine Learning Approach to Go Lin Wu, Pierre Baldi

Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds Gloria Haro, Gregory Randall, Guillermo Sapiro

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation Yee Teh, David Newman, Max Welling

Dynamic Foreground/Background Extraction from Images and Videos using Random Patches Le Lu, Gregory Hager

Subordinate class recognition using relational object models Aharon Hillel, Daphna Weinshall

Dirichlet-Enhanced Spam Filtering based on Biased Samples Steffen Bickel, Tobias Scheffer

Stability of $K$-Means Clustering Alexander Rakhlin, Andrea Caponnetto

Convergence of Laplacian Eigenmaps Mikhail Belkin, Partha Niyogi

Bayesian Policy Gradient Algorithms Mohammad Ghavamzadeh, Yaakov Engel

Handling Advertisements of Unknown Quality in Search Advertising Sandeep Pandey, Christopher Olston

Part-based Probabilistic Point Matching using Equivalence Constraints Graham Mcneill, Sethu Vijayakumar

Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle

Optimal Change-Detection and Spiking Neurons Angela J. Yu

Temporal dynamics of information content carried by neurons in the primary visual cortex Danko Nikolić, Stefan Haeusler, Wolf Singer, Wolfgang Maass

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

Automated Hierarchy Discovery for Planning in Partially Observable Environments Laurent Charlin, Pascal Poupart, Romy Shioda

Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models Mark Johnson, Thomas Griffiths, Sharon Goldwater

On Transductive Regression Corinna Cortes, Mehryar Mohri

Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis Amit Gore, Shantanu Chakrabartty

Comparative Gene Prediction using Conditional Random Fields Jade Vinson, David Decaprio, Matthew Pearson, Stacey Luoma, James Galagan

Learning annotated hierarchies from relational data Daniel M. Roy, Charles Kemp, Vikash Mansinghka, Joshua Tenenbaum

Single Channel Speech Separation Using Factorial Dynamics John Hershey, Trausti Kristjansson, Steven Rennie, Peder A. Olsen

A Small World Threshold for Economic Network Formation Eyal Even-dar, Michael Kearns

iLSTD: Eligibility Traces and Convergence Analysis Alborz Geramifard, Michael Bowling, Martin Zinkevich, Richard S. Sutton

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets Jerónimo Arenas-garcía, Kaare Petersen, Lars K. Hansen

Data Integration for Classification Problems Employing Gaussian Process Priors Mark Girolami, Mingjun Zhong

Stochastic Relational Models for Discriminative Link Prediction Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu

Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces Moritz Grosse-wentrup, Klaus Gramann, Martin Buss

A recipe for optimizing a time-histogram Hideaki Shimazaki, Shigeru Shinomoto

Inducing Metric Violations in Human Similarity Judgements Julian Laub, Klaus-Robert Müller, Felix A. Wichmann, Jakob H. Macke

Nonnegative Sparse PCA Ron Zass, Amnon Shashua

Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons Elisabetta Chicca, Giacomo Indiveri, Rodney Douglas

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

Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space Wenye Li, Kin-hong Lee, Kwong-sak Leung

Map-Reduce for Machine Learning on Multicore Cheng-tao Chu, Sang Kim, Yi-an Lin, Yuanyuan Yu, Gary Bradski, Kunle Olukotun, Andrew Ng

Natural Actor-Critic for Road Traffic Optimisation Silvia Richter, Douglas Aberdeen, Jin Yu

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions Christian Walder, Olivier Chapelle, Bernhard Schölkopf

Multiple Instance Learning for Computer Aided Diagnosis Murat Dundar, Balaji Krishnapuram, R. Rao, Glenn Fung

A selective attention multi--chip system with dynamic synapses and spiking neurons Chiara Bartolozzi, Giacomo Indiveri

Real-time adaptive information-theoretic optimization of neurophysiology experiments Jeremy Lewi, Robert Butera, Liam Paninski

High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression Martin J. Wainwright, John Lafferty, Pradeep Ravikumar

Efficient Learning of Sparse Representations with an Energy-Based Model Marc'aurelio Ranzato, Christopher Poultney, Sumit Chopra, Yann Cun

Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models Alexander Ihler, Padhraic Smyth

Using Combinatorial Optimization within Max-Product Belief Propagation Daniel Tarlow, Gal Elidan, Daphne Koller, John C. Duchi

Branch and Bound for Semi-Supervised Support Vector Machines Olivier Chapelle, Vikas Sindhwani, S. Keerthi

Differential Entropic Clustering of Multivariate Gaussians Jason Davis, Inderjit Dhillon

Multi-Instance Multi-Label Learning with Application to Scene Classification Zhi-Li Zhang, Min-ling Zhang

Analysis of Contour Motions Ce Liu, William Freeman, Edward Adelson

Learning to be Bayesian without Supervision Martin Raphan, Eero Simoncelli

Causal inference in sensorimotor integration Konrad Körding, Joshua Tenenbaum

A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida

Approximate inference using planar graph decomposition Amir Globerson, Tommi Jaakkola

Context Effects in Category Learning: An Investigation of Four Probabilistic Models Michael C. Mozer, Michael Shettel, Michael Holmes

An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Ng

Parameter Expanded Variational Bayesian Methods Tommi Jaakkola, Yuan Qi

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments Michael Mandel, Daniel Ellis, Tony Jebara

Recursive ICA Honghao Shan, Lingyun Zhang, Garrison Cottrell

The Neurodynamics of Belief Propagation on Binary Markov Random Fields Thomas Ott, Ruedi Stoop

Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing Yuanhao Chen, Long Zhu, Alan L. Yuille

A Humanlike Predictor of Facial Attractiveness Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-or, Eytan Ruppin

Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype Tobias Sing, Niko Beerenwinkel

Image Retrieval and Classification Using Local Distance Functions Andrea Frome, Yoram Singer, Jitendra Malik

Chained Boosting Christian Shelton, Wesley Huie, Kin Kan

Support Vector Machines on a Budget Ofer Dekel, Yoram Singer

Manifold Denoising Matthias Hein, Markus Maier

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner

Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds Benjamin Rubinstein, Peter Bartlett, J. Rubinstein

Learning to parse images of articulated bodies Deva Ramanan

Correcting Sample Selection Bias by Unlabeled Data Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, Alex Smola

A Nonparametric Approach to Bottom-Up Visual Saliency Wolf Kienzle, Felix A. Wichmann, Matthias Franz, Bernhard Schölkopf

Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees Konrad Rieck, Pavel Laskov, Sören Sonnenburg

Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension Manfred K. K. Warmuth, Dima Kuzmin

Efficient Structure Learning of Markov Networks using $L_1$-Regularization Su-in Lee, Varun Ganapathi, Daphne Koller

Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions Philip Long, Rocco Servedio

Mixture Regression for Covariate Shift Masashi Sugiyama, Amos J. Storkey

implicit Online Learning with Kernels Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli, S.v.n. Vishwanathan

PG-means: learning the number of clusters in data Yu Feng, Greg Hamerly

Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data Ping Li, Kenneth Church, Trevor Hastie

Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games Chris Murray, Geoffrey J. Gordon

Optimal Single-Class Classification Strategies Ran El-Yaniv, Mordechai Nisenson

Learning to Rank with Nonsmooth Cost Functions Christopher Burges, Robert Ragno, Quoc Le

Analysis of Representations for Domain Adaptation Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira

Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation Jason Samonds, Brian Potetz, Tai Lee

Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation Gavin Cawley, Nicola Talbot, Mark Girolami

Gaussian and Wishart Hyperkernels Risi Kondor, Tony Jebara

A Complexity-Distortion Approach to Joint Pattern Alignment Andrea Vedaldi, Stefano Soatto

AdaBoost is Consistent Peter Bartlett, Mikhail Traskin

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods Matthias Seeger

Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning Gediminas Lukšys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner

A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems David Barber, Bertrand Mesot

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons Stefan Klampfl, Wolfgang Maass, Robert Legenstein

A Theory of Retinal Population Coding Eizaburo Doi, Michael Lewicki

An Approach to Bounded Rationality Eli Ben-sasson, Ehud Kalai, Adam Kalai

Fundamental Limitations of Spectral Clustering Boaz Nadler, Meirav Galun

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning Hamed Valizadegan, Rong Jin

Clustering Under Prior Knowledge with Application to Image Segmentation Dong Cheng, Vittorio Murino, Mário Figueiredo

Inferring Network Structure from Co-Occurrences Michael Rabbat, Mário Figueiredo, Robert Nowak

Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning Peter Auer, Ronald Ortner

Fast Iterative Kernel PCA Nicol Schraudolph, Simon Günter, S.v.n. Vishwanathan

Uncertainty, phase and oscillatory hippocampal recall Máté Lengyel, Peter Dayan

Speakers optimize information density through syntactic reduction T. Jaeger, Roger Levy

Learning Structural Equation Models for fMRI Enrico Simonotto, Heather Whalley, Stephen Lawrie, Lawrence Murray, David Mcgonigle, Amos J. Storkey

Simplifying Mixture Models through Function Approximation Kai Zhang, James Kwok

Sparse Representation for Signal Classification Ke Huang, Selin Aviyente

Similarity by Composition Oren Boiman, Michal Irani

An Information Theoretic Framework for Eukaryotic Gradient Sensing Joseph Kimmel, Richard Salter, Peter Thomas

Prediction on a Graph with a Perceptron Mark Herbster, Massimiliano Pontil

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models S. Keerthi, Vikas Sindhwani, Olivier Chapelle

Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization Rey Ramírez, Jason Palmer, Scott Makeig, Bhaskar Rao, David Wipf

Efficient Methods for Privacy Preserving Face Detection Shai Avidan, Moshe Butman

Balanced Graph Matching Timothee Cour, Praveen Srinivasan, Jianbo Shi

Fast Discriminative Visual Codebooks using Randomized Clustering Forests Frank Moosmann, Bill Triggs, Frederic Jurie

Learning Motion Style Synthesis from Perceptual Observations Lorenzo Torresani, Peggy Hackney, Christoph Bregler

Linearly-solvable Markov decision problems Emanuel Todorov

Learning on Graph with Laplacian Regularization Rie Ando, Tong Zhang

An Oracle Inequality for Clipped Regularized Risk Minimizers Ingo Steinwart, Don Hush, Clint Scovel

Clustering appearance and shape by learning jigsaws Anitha Kannan, John Winn, Carsten Rother

Large Margin Component Analysis Lorenzo Torresani, Kuang-chih Lee

Kernels on Structured Objects Through Nested Histograms Marco Cuturi, Kenji Fukumizu

Learning with Hypergraphs: Clustering, Classification, and Embedding Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf

Learning Dense 3D Correspondence Florian Steinke, Volker Blanz, Bernhard Schölkopf

Fast Computation of Graph Kernels Karsten Borgwardt, Nicol Schraudolph, S.v.n. Vishwanathan

Multi-dynamic Bayesian Networks Karim Filali, Jeff A. Bilmes

Max-margin classification of incomplete data Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

Scalable Discriminative Learning for Natural Language Parsing and Translation Joseph Turian, Benjamin Wellington, I. Melamed

On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts Hariharan Narayanan, Mikhail Belkin, Partha Niyogi

A Kernel Method for the Two-Sample-Problem Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alex Smola

Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers

Emergence of conjunctive visual features by quadratic independent component analysis J.t. Lindgren, Aapo Hyvärinen

Nonlinear physically-based models for decoding motor-cortical population activity Gregory Shakhnarovich, Sung-phil Kim, Michael Black

Conditional mean field Peter Carbonetto, Nando Freitas

Unsupervised Regression with Applications to Nonlinear System Identification Ali Rahimi, Ben Recht

Large Margin Hidden Markov Models for Automatic Speech Recognition Fei Sha, Lawrence Saul

No-regret Algorithms for Online Convex Programs Geoffrey J. Gordon

A PAC-Bayes Risk Bound for General Loss Functions Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand

Distributed Inference in Dynamical Systems Stanislav Funiak, Carlos Guestrin, Rahul Sukthankar, Mark Paskin

Modelling transcriptional regulation using Gaussian Processes Neil Lawrence, Guido Sanguinetti, Magnus Rattray

TrueSkill™: A Bayesian Skill Rating System Ralf Herbrich, Tom Minka, Thore Graepel

Learnability and the doubling dimension Yi Li, Philip Long

Sample Complexity of Policy Search with Known Dynamics Peter Bartlett, Ambuj Tewari

Large Scale Hidden Semi-Markov SVMs Gunnar Rätsch, Sören Sonnenburg

MLLE: Modified Locally Linear Embedding Using Multiple Weights Zhenyue Zhang, Jing Wang

Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms Xinhua Zhang, Wee Lee

Boosting Structured Prediction for Imitation Learning J. Bagnell, Joel Chestnutt, David Bradley, Nathan Ratliff

Denoising and Dimension Reduction in Feature Space Mikio Braun, Klaus-Robert Müller, Joachim Buhmann

Relational Learning with Gaussian Processes Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Keerthi

Advances in Neural Information Processing Systems 19 (NIPS 2006)

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