Book
Advances in Neural Information Processing Systems 21 (NIPS 2008)
Edited by:
D. Koller and D. Schuurmans and Y. Bengio and L. Bottou
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
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