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Advances in Neural Information Processing Systems 21 (NIPS 2008)

Edited by: D. Koller and D. Schuurmans and Y. Bengio and L. Bottou

Purchase Printed Proceeding

ISBN: 9781605609492

Near-minimax recursive density estimation on the binary hypercube Maxim Raginsky, Svetlana Lazebnik, Rebecca Willett, Jorge Silva
Translated Learning: Transfer Learning across Different Feature Spaces Wenyuan Dai, Yuqiang Chen, Gui-rong Xue, Qiang Yang, Yong Yu
Learning Bounded Treewidth Bayesian Networks Gal Elidan, Stephen Gould
Local Gaussian Process Regression for Real Time Online Model Learning Duy Nguyen-tuong, Jan Peters, Matthias Seeger
Grouping Contours Via a Related Image Praveen Srinivasan, Liming Wang, Jianbo Shi
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds Jeremy Lewi, Robert Butera, David Schneider, Sarah Woolley, Liam Paninski
Analyzing human feature learning as nonparametric Bayesian inference Thomas Griffiths, Joseph Austerweil
From Online to Batch Learning with Cutoff-Averaging Ofer Dekel
Structured ranking learning using cumulative distribution networks Jim Huang, Brendan J. Frey
Asynchronous Distributed Learning of Topic Models Padhraic Smyth, Max Welling, Arthur Asuncion
Cascaded Classification Models: Combining Models for Holistic Scene Understanding Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daphne Koller
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes Ben Calderhead, Mark Girolami, Neil Lawrence
Linear Classification and Selective Sampling Under Low Noise Conditions Giovanni Cavallanti, Nicolò Cesa-bianchi, Claudio Gentile
On the Efficient Minimization of Classification Calibrated Surrogates Richard Nock, Frank Nielsen
Unlabeled data: Now it helps, now it doesn't Aarti Singh, Robert Nowak, Jerry Zhu
Unifying the Sensory and Motor Components of Sensorimotor Adaptation Adrian Haith, Carl Jackson, R. Miall, Sethu Vijayakumar
Modeling human function learning with Gaussian processes Thomas Griffiths, Chris Lucas, Joseph Williams, Michael Kalish
Hebbian Learning of Bayes Optimal Decisions Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis Gabriele Schweikert, Gunnar Rätsch, Christian Widmer, Bernhard Schölkopf
Kernel Change-point Analysis Zaïd Harchaoui, Eric Moulines, Francis Bach
Biasing Approximate Dynamic Programming with a Lower Discount Factor Marek Petrik, Bruno Scherrer
Performance analysis for L\_2 kernel classification Jooseuk Kim, Clayton Scott
Influence of graph construction on graph-based clustering measures Markus Maier, Ulrike Luxburg, Matthias Hein
MDPs with Non-Deterministic Policies M. Fard, Joelle Pineau
Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization Liu Yang, Rong Jin, Rahul Sukthankar
Evaluating probabilities under high-dimensional latent variable models Iain Murray, Russ R. Salakhutdinov
Counting Solution Clusters in Graph Coloring Problems Using Belief Propagation Lukas Kroc, Ashish Sabharwal, Bart Selman
Supervised Bipartite Graph Inference Yoshihiro Yamanishi
Domain Adaptation with Multiple Sources Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning Ali Rahimi, Benjamin Recht
Regularized Learning with Networks of Features Ted Sandler, John Blitzer, Partha Talukdar, Lyle Ungar
Breaking Audio CAPTCHAs Jennifer Tam, Jiri Simsa, Sean Hyde, Luis Ahn
Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection Takafumi Kanamori, Shohei Hido, Masashi Sugiyama
Differentiable Sparse Coding J. Bagnell, David Bradley
Inferring rankings under constrained sensing Srikanth Jagabathula, Devavrat Shah
Sparse Convolved Gaussian Processes for Multi-output Regression Mauricio Alvarez, Neil Lawrence
A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context Abhinav Gupta, Jianbo Shi, Larry S. Davis
Multi-task Gaussian Process Learning of Robot Inverse Dynamics Christopher Williams, Stefan Klanke, Sethu Vijayakumar, Kian Chai
Efficient Inference in Phylogenetic InDel Trees Alexandre Bouchard-côté, Dan Klein, Michael Jordan
Estimating vector fields using sparse basis field expansions Stefan Haufe, Vadim Nikulin, Andreas Ziehe, Klaus-Robert Müller, Guido Nolte
Probabilistic detection of short events, with application to critical care monitoring Norm Aleks, Stuart J. Russell, Michael Madden, Diane Morabito, Kristan Staudenmayer, Mitchell Cohen, Geoffrey Manley
Spectral Clustering with Perturbed Data Ling Huang, Donghui Yan, Nina Taft, Michael Jordan
Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG Julia Owen, Hagai Attias, Kensuke Sekihara, Srikantan Nagarajan, David Wipf
Multi-stage Convex Relaxation for Learning with Sparse Regularization Tong Zhang
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick Kay, Jack Gallant, Pradeep Ravikumar
A Scalable Hierarchical Distributed Language Model Andriy Mnih, Geoffrey E. Hinton
Supervised Exponential Family Principal Component Analysis via Convex Optimization Yuhong Guo
Stochastic Relational Models for Large-scale Dyadic Data using MCMC Shenghuo Zhu, Kai Yu, Yihong Gong
Online Models for Content Optimization Deepak Agarwal, Bee-chung Chen, Pradheep Elango, Nitin Motgi, Seung-taek Park, Raghu Ramakrishnan, Scott Roy, Joe Zachariah
Robust Regression and Lasso Huan Xu, Constantine Caramanis, Shie Mannor
Hierarchical Fisher Kernels for Longitudinal Data Zhengdong Lu, Jeffrey Kaye, Todd Leen
Correlated Bigram LSA for Unsupervised Language Model Adaptation Yik-cheung Tam, Tanja Schultz
The Infinite Factorial Hidden Markov Model Jurgen Gael, Yee Teh, Zoubin Ghahramani
Sparse Signal Recovery Using Markov Random Fields Volkan Cevher, Marco Duarte, Chinmay Hegde, Richard Baraniuk
Clustering via LP-based Stabilities Nikos Komodakis, Nikos Paragios, Georgios Tziritas
Spike Feature Extraction Using Informative Samples Zhi Yang, Qi Zhao, Wentai Liu
Fast Computation of Posterior Mode in Multi-Level Hierarchical Models Liang Zhang, Deepak Agarwal
An improved estimator of Variance Explained in the presence of noise Ralf Haefner, Bruce Cumming
The Infinite Hierarchical Factor Regression Model Piyush Rai, Hal Daume
Deep Learning with Kernel Regularization for Visual Recognition Kai Yu, Wei Xu, Yihong Gong
Learning Transformational Invariants from Natural Movies Charles Cadieu, Bruno Olshausen
On Bootstrapping the ROC Curve Patrice Bertail, Stéphan Clémençcon, Nicolas Vayatis
QUIC-SVD: Fast SVD Using Cosine Trees Michael Holmes, Jr. Isbell, Charles Lee, Alexander Gray
A Massively Parallel Digital Learning Processor Hans Graf, Srihari Cadambi, Venkata Jakkula, Murugan Sankaradass, Eric Cosatto, Srimat Chakradhar, Igor Dourdanovic
Characterizing response behavior in multisensory perception with conflicting cues Rama Natarajan, Iain Murray, Ladan Shams, Richard Zemel
The Gaussian Process Density Sampler Iain Murray, David MacKay, Ryan P. Adams
Cyclizing Clusters via Zeta Function of a Graph Deli Zhao, Xiaoou Tang
Integrating Locally Learned Causal Structures with Overlapping Variables David Danks, Clark Glymour, Robert Tillman
A mixture model for the evolution of gene expression in non-homogeneous datasets Gerald Quon, Yee Teh, Esther Chan, Timothy Hughes, Michael Brudno, Quaid Morris
An Homotopy Algorithm for the Lasso with Online Observations Pierre Garrigues, Laurent Ghaoui
Adaptive Martingale Boosting Phil Long, Rocco Servedio
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method Dongryeol Lee, Alexander Gray
ICA based on a Smooth Estimation of the Differential Entropy Lev Faivishevsky, Jacob Goldberger
Support Vector Machines with a Reject Option Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu
Generative versus discriminative training of RBMs for classification of fMRI images Tanya Schmah, Geoffrey E. Hinton, Steven Small, Stephen Strother, Richard Zemel
Particle Filter-based Policy Gradient in POMDPs Pierre-arnaud Coquelin, Romain Deguest, Rémi Munos
Algorithms for Infinitely Many-Armed Bandits Yizao Wang, Jean-yves Audibert, Rémi Munos
On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor Christoph Kolodziejski, Bernd Porr, Minija Tamosiunaite, Florentin Wörgötter
Gates Tom Minka, John Winn
Multi-Level Active Prediction of Useful Image Annotations for Recognition Sudheendra Vijayanarasimhan, Kristen Grauman
MAS: a multiplicative approximation scheme for probabilistic inference Ydo Wexler, Christopher Meek
Learning Hybrid Models for Image Annotation with Partially Labeled Data Xuming He, Richard Zemel
Efficient Sampling for Gaussian Process Inference using Control Variables Neil Lawrence, Magnus Rattray, Michalis Titsias
An Online Algorithm for Maximizing Submodular Functions Matthew Streeter, Daniel Golovin
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
Bayesian Exponential Family PCA Shakir Mohamed, Zoubin Ghahramani, Katherine A. Heller
Sequential effects: Superstition or rational behavior? Angela J. Yu, Jonathan D. Cohen
PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning Chunhua Shen, Alan Welsh, Lei Wang
Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control Lavi Shpigelman, Hagai Lalazar, Eilon Vaadia
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE Garvesh Raskutti, Bin Yu, Martin J. Wainwright, Pradeep Ravikumar
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning Carmen Sandi, Wulfram Gerstner, Gediminas Lukšys
How memory biases affect information transmission: A rational analysis of serial reproduction Jing Xu, Thomas Griffiths
Diffeomorphic Dimensionality Reduction Christian Walder, Bernhard Schölkopf
Using Bayesian Dynamical Systems for Motion Template Libraries Silvia Chiappa, Jens Kober, Jan Peters
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering Dilan Gorur, Yee Teh
Bounding Performance Loss in Approximate MDP Homomorphisms Jonathan Taylor, Doina Precup, Prakash Panagaden
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks Alex Graves, Jürgen Schmidhuber
Robust Near-Isometric Matching via Structured Learning of Graphical Models Alex Smola, Julian Mcauley, Tibério Caetano
Fast Prediction on a Tree Mark Herbster, Massimiliano Pontil, Sergio Galeano
Exact Convex Confidence-Weighted Learning Koby Crammer, Mark Dredze, Fernando Pereira
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction Fabian Sinz, Matthias Bethge
Regularized Co-Clustering with Dual Supervision Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovic
Tighter Bounds for Structured Estimation Olivier Chapelle, Chuong B., Choon Teo, Quoc Le, Alex Smola
Multi-Agent Filtering with Infinitely Nested Beliefs Luke Zettlemoyer, Brian Milch, Leslie Kaelbling
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie Luo, Holly Jimison, Frank Ohl, Misha Pavel
Look Ma, No Hands: Analyzing the Monotonic Feature Abstraction for Text Classification Doug Downey, Oren Etzioni
Nonparametric regression and classification with joint sparsity constraints Han Liu, Larry Wasserman, John Lafferty
Recursive Segmentation and Recognition Templates for 2D Parsing Leo Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan L. Yuille
Predicting the Geometry of Metal Binding Sites from Protein Sequence Paolo Frasconi, Andrea Passerini
Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons Adam Ponzi, Jeff Wickens
High-dimensional support union recovery in multivariate regression Guillaume R. Obozinski, Martin J. Wainwright, Michael Jordan
Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm Andrew Smith, Hongyuan Zha, Xiao-ming Wu
A Convex Upper Bound on the Log-Partition Function for Binary Distributions Laurent Ghaoui, Assane Gueye
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models Tong Zhang
Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking Nir Ailon
Theory of matching pursuit Zakria Hussain, John Shawe-taylor
Policy Search for Motor Primitives in Robotics Jens Kober, Jan Peters
Mortal Multi-Armed Bandits Deepayan Chakrabarti, Ravi Kumar, Filip Radlinski, Eli Upfal
Adapting to a Market Shock: Optimal Sequential Market-Making Sanmay Das, Malik Magdon-Ismail
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification Simon Lacoste-Julien, Fei Sha, Michael Jordan
Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing Moritz Grosse-wentrup
Rademacher Complexity Bounds for Non-I.I.D. Processes Mehryar Mohri, Afshin Rostamizadeh
A rational model of preference learning and choice prediction by children Christopher Lucas, Thomas Griffiths, Fei Xu, Christine Fawcett
An ideal observer model of infant object perception Charles Kemp, Fei Xu
Empirical performance maximization for linear rank statistics Stéphan Clémençcon, Nicolas Vayatis
Resolution Limits of Sparse Coding in High Dimensions Sundeep Rangan, Vivek Goyal, Alyson K. Fletcher
Privacy-preserving logistic regression Kamalika Chaudhuri, Claire Monteleoni
Efficient Exact Inference in Planar Ising Models Nicol Schraudolph, Dmitry Kamenetsky
Deflation Methods for Sparse PCA Lester Mackey
Mixed Membership Stochastic Blockmodels Edo M. Airoldi, David Blei, Stephen Fienberg, Eric Xing
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes Erik Sudderth, Michael Jordan
Shape-Based Object Localization for Descriptive Classification Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform Guangzhi Cao, Charles Bouman
Characterizing neural dependencies with copula models Pietro Berkes, Frank Wood, Jonathan Pillow
Learning with Consistency between Inductive Functions and Kernels Haixuan Yang, Irwin King, Michael Lyu
Syntactic Topic Models Jordan Boyd-graber, David Blei
A general framework for investigating how far the decoding process in the brain can be simplified Masafumi Oizumi, Toshiyuki Ishii, Kazuya Ishibashi, Toshihiko Hosoya, Masato Okada
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms John Roberts, Russ Tedrake
Artificial Olfactory Brain for Mixture Identification Mehmet Muezzinoglu, Alexander Vergara, Ramon Huerta, Thomas Nowotny, Nikolai Rulkov, Henry Abarbanel, Allen Selverston, Mikhail Rabinovich
Robust Kernel Principal Component Analysis Minh Nguyen, Fernando Torre
Relative Margin Machines Tony Jebara, Pannagadatta Shivaswamy
Bayesian Kernel Shaping for Learning Control Jo-anne Ting, Mrinal Kalakrishnan, Sethu Vijayakumar, Stefan Schaal
An Extended Level Method for Efficient Multiple Kernel Learning Zenglin Xu, Rong Jin, Irwin King, Michael Lyu
Sparse Online Learning via Truncated Gradient John Langford, Lihong Li, Tong Zhang
Bayesian Model of Behaviour in Economic Games Debajyoti Ray, Brooks King-casas, P. Montague, Peter Dayan
Skill Characterization Based on Betweenness Özgür Şimşek, Andrew Barto
Improved Moves for Truncated Convex Models Philip Torr, M. Kumar
Kernelized Sorting Novi Quadrianto, Le Song, Alex Smola
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice Zhihua Zhang, Michael Jordan, Dit-Yan Yeung
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems Emily Fox, Erik Sudderth, Michael Jordan, Alan Willsky
Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement Michael Todd, Yael Niv, Jonathan D. Cohen
Optimization on a Budget: A Reinforcement Learning Approach Paul Ruvolo, Ian Fasel, Javier Movellan
Dependent Dirichlet Process Spike Sorting Jan Gasthaus, Frank Wood, Dilan Gorur, Yee Teh
The Recurrent Temporal Restricted Boltzmann Machine Ilya Sutskever, Geoffrey E. Hinton, Graham W. Taylor
Short-Term Depression in VLSI Stochastic Synapse Peng Xu, Timothy Horiuchi, Pamela Abshire
Generative and Discriminative Learning with Unknown Labeling Bias Steven Phillips, Miroslav Dudík
Large Margin Taxonomy Embedding for Document Categorization Kilian Q. Weinberger, Olivier Chapelle
Modeling the effects of memory on human online sentence processing with particle filters Roger Levy, Florencia Reali, Thomas Griffiths
Clusters and Coarse Partitions in LP Relaxations David Sontag, Amir Globerson, Tommi Jaakkola
Bounds on marginal probability distributions Joris M. Mooij, Hilbert Kappen
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation Indraneel Mukherjee, David Blei
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning Francis Bach
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features Tae-kyun Kim, Roberto Cipolla
Load and Attentional Bayes Peter Dayan
Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 Klaus Wimmer, Marcel Stimberg, Robert Martin, Lars Schwabe, Jorge Mariño, James Schummers, David Lyon, Mriganka Sur, Klaus Obermayer
An interior-point stochastic approximation method and an L1-regularized delta rule Peter Carbonetto, Mark Schmidt, Nando Freitas
Dynamic visual attention: searching for coding length increments Xiaodi Hou, Liqing Zhang
Phase transitions for high-dimensional joint support recovery Sahand Negahban, Martin J. Wainwright
Online Metric Learning and Fast Similarity Search Prateek Jain, Brian Kulis, Inderjit Dhillon, Kristen Grauman
Bayesian Network Score Approximation using a Metagraph Kernel Benjamin Yackley, Eduardo Corona, Terran Lane
Fast Rates for Regularized Objectives Karthik Sridharan, Shai Shalev-shwartz, Nathan Srebro
Bayesian Synchronous Grammar Induction Phil Blunsom, Trevor Cohn, Miles Osborne
Tracking Changing Stimuli in Continuous Attractor Neural Networks K. Wong, Si Wu, Chi Fung
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity Byron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen Ryu, Krishna V. Shenoy, Maneesh Sahani
Kernel Measures of Independence for non-iid Data Xinhua Zhang, Le Song, Arthur Gretton, Alex Smola
Regularized Policy Iteration Amir Farahmand, Mohammad Ghavamzadeh, Shie Mannor, Csaba Szepesvári
Dimensionality Reduction for Data in Multiple Feature Representations Yen-yu Lin, Tyng-luh Liu, Chiou-shann Fuh
Continuously-adaptive discretization for message-passing algorithms Michael Isard, John MacCormick, Kannan Achan
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing Benjamin Schrauwen, Lars Buesing, Robert Legenstein
Mind the Duality Gap: Logarithmic regret algorithms for online optimization Shai Shalev-shwartz, Sham M. Kakade
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data Tran Truyen, Dinh Phung, Hung Bui, Svetha Venkatesh
A spatially varying two-sample recombinant coalescent, with applications to HIV escape response Alexander Braunstein, Zhi Wei, Shane Jensen, Jon Mcauliffe
Measures of Clustering Quality: A Working Set of Axioms for Clustering Shai Ben-David, Margareta Ackerman
Structure Learning in Human Sequential Decision-Making Daniel Acuna, Paul R. Schrater
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Biessmann, Bernhard Schölkopf
Supervised Dictionary Learning Julien Mairal, Jean Ponce, Guillermo Sapiro, Andrew Zisserman, Francis Bach
Natural Image Denoising with Convolutional Networks Viren Jain, Sebastian Seung
Optimal Response Initiation: Why Recent Experience Matters Matt Jones, Sachiko Kinoshita, Michael C. Mozer
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf, Matthias Seeger
Temporal Dynamics of Cognitive Control Jeremy Reynolds, Michael C. Mozer
Overlaying classifiers: a practical approach for optimal ranking Stéphan Clémençcon, Nicolas Vayatis
Model selection and velocity estimation using novel priors for motion patterns Shuang Wu, Hongjing Lu, Alan L. Yuille
Estimation of Information Theoretic Measures for Continuous Random Variables Fernando Pérez-Cruz
On the Reliability of Clustering Stability in the Large Sample Regime Ohad Shamir, Naftali Tishby
Using matrices to model symbolic relationship Ilya Sutskever, Geoffrey E. Hinton
Psychiatry: Insights into depression through normative decision-making models Quentin Huys, Joshua Vogelstein, Peter Dayan
Characteristic Kernels on Groups and Semigroups Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur
Multi-label Multiple Kernel Learning Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye
Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl Juan Huo, Zhijun Yang, Alan Murray
Spectral Hashing Yair Weiss, Antonio Torralba, Rob Fergus
Multi-resolution Exploration in Continuous Spaces Ali Nouri, Michael Littman
A computational model of hippocampal function in trace conditioning Elliot Ludvig, Richard S. Sutton, Eric Verbeek, E. Kehoe
Online Prediction on Large Diameter Graphs Mark Herbster, Guy Lever, Massimiliano Pontil
Sparse probabilistic projections Cédric Archambeau, Francis Bach
Sparsity of SVMs that use the epsilon-insensitive loss Ingo Steinwart, Andreas Christmann
Automatic online tuning for fast Gaussian summation Vlad Morariu, Balaji Srinivasan, Vikas C. Raykar, Ramani Duraiswami, Larry S. Davis
Reducing statistical dependencies in natural signals using radial Gaussianization Siwei Lyu, Eero Simoncelli
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning Massih R. Amini, Nicolas Usunier, François Laviolette
Nonrigid Structure from Motion in Trajectory Space Ijaz Akhter, Yaser Sheikh, Sohaib Khan, Takeo Kanade
Transfer Learning by Distribution Matching for Targeted Advertising Steffen Bickel, Christoph Sawade, Tobias Scheffer
A Convergent $O(n)$ Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation Richard S. Sutton, Hamid Maei, Csaba Szepesvári
Estimating Robust Query Models with Convex Optimization Kevyn Collins-thompson
Learning Taxonomies by Dependence Maximization Matthew Blaschko, Arthur Gretton
Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets Jean-philippe Pellet, André Elisseeff
Goal-directed decision making in prefrontal cortex: a computational framework Matthew Botvinick, James An
Localized Sliced Inverse Regression Qiang Wu, Sayan Mukherjee, Feng Liang
Near-optimal Regret Bounds for Reinforcement Learning Peter Auer, Thomas Jaksch, Ronald Ortner
Non-parametric Regression Between Manifolds Florian Steinke, Matthias Hein
Unsupervised Learning of Visual Sense Models for Polysemous Words Kate Saenko, Trevor Darrell
Extended Grassmann Kernels for Subspace-Based Learning Jihun Hamm, Daniel Lee
Implicit Mixtures of Restricted Boltzmann Machines Vinod Nair, Geoffrey E. Hinton
Self-organization using synaptic plasticity Vicençc Gómez, Andreas Kaltenbrunner, Vicente López, Hilbert Kappen
Interpreting the neural code with Formal Concept Analysis Dominik Endres, Peter Foldiak
Global Ranking Using Continuous Conditional Random Fields Tao Qin, Tie-yan Liu, Xu-dong Zhang, De-sheng Wang, Hang Li
Improving on Expectation Propagation Manfred Opper, Ulrich Paquet, Ole Winther
Learning a discriminative hidden part model for human action recognition Yang Wang, Greg Mori
Adaptive Template Matching with Shift-Invariant Semi-NMF Jonathan Roux, Alain Cheveigné, Lucas Parra
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Masato Okada
Partially Observed Maximum Entropy Discrimination Markov Networks Jun Zhu, Eric Xing, Bo Zhang
Playing Pinball with non-invasive BCI Matthias Krauledat, Konrad Grzeska, Max Sagebaum, Benjamin Blankertz, Carmen Vidaurre, Klaus-Robert Müller, Michael Schröder
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction Shay Cohen, Kevin Gimpel, Noah A. Smith
Risk Bounds for Randomized Sample Compressed Classifiers Mohak Shah
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text Yi Zhang, Artur Dubrawski, Jeff Schneider
Online Optimization in X-Armed Bandits Sébastien Bubeck, Gilles Stoltz, Csaba Szepesvári, Rémi Munos
Variational Mixture of Gaussian Process Experts Chao Yuan, Claus Neubauer
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost Hamed Masnadi-shirazi, Nuno Vasconcelos
Non-stationary dynamic Bayesian networks Joshua Robinson, Alexander Hartemink
Nonlinear causal discovery with additive noise models Patrik Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf
Simple Local Models for Complex Dynamical Systems Erik Talvitie, Satinder Singh
Fitted Q-iteration by Advantage Weighted Regression Gerhard Neumann, Jan Peters
On the Generalization Ability of Online Strongly Convex Programming Algorithms Sham M. Kakade, Ambuj Tewari
Multiscale Random Fields with Application to Contour Grouping Longin Latecki, Chengen Lu, Marc Sobel, Xiang Bai
Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex Arno Onken, Steffen Grünewälder, Matthias Munk, Klaus Obermayer
Predictive Indexing for Fast Search Sharad Goel, John Langford, Alexander Strehl
Human Active Learning Rui Castro, Charles Kalish, Robert Nowak, Ruichen Qian, Tim Rogers, Jerry Zhu
Clustered Multi-Task Learning: A Convex Formulation Laurent Jacob, Jean-philippe Vert, Francis Bach
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation Dotan Castro, Dmitry Volkinshtein, Ron Meir
One sketch for all: Theory and Application of Conditional Random Sampling Ping Li, Kenneth Church, Trevor Hastie
The Mondrian Process Daniel M. Roy, Yee Teh
Scalable Algorithms for String Kernels with Inexact Matching Pavel Kuksa, Pai-hsi Huang, Vladimir Pavlovic

Advances in Neural Information Processing Systems 21 (NIPS 2008)

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