NIPS : Conferences : 2008 : Program

Schedule

Conference Sessions (December 8-11, 2008)

Monday
6:30 - 7:30pm	Opening Banquet
7:45 - 8:25pm	Oral session 1: ClusteringSession Chair:Fei Sha
	S. Ben-David, M. Ackerman Measures of Clustering Quality: A Working Set of Axioms for Clustering M. Maier, U. von Luxburg, M. Hein Influence of graph construction on graph-based clustering measures
8:25 - 8:45pm	Spotlights
	O. Shamir, N. Tishby On the Reliability of Clustering Stability in the Large Sample Regime L. Huang, D. Yan, M. Jordan, N. Taft Spectral Clustering with Perturbed Data A. Gupta, J. Shi, L. Davis A "Shape Aware'' Model for semi-supervised Learning of Objects and its Context P. Li, K. Church, T. Hastie One sketch for all: Theory and Application of Conditional Random Sampling T. Minka, J. Winn Gates D. Agarwal, L. Zhang Fast Computation of Posterior Mode in Multi-Level Hierarchical Models I. Mukherjee, D. Blei Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation A. Bouchard-Côté, M. Jordan, D. Klein Efficient Inference in Phylogenetic InDel Trees K. Weinberger, O. Chapelle Large Margin Taxonomy Embedding for Document Categorization D. Downey, O. Etzioni Analyzing the Monotonic Feature Abstraction for Text Classification J. Boyd-Graber, D. Blei Syntactic Topic Models L. Yang, R. Jin, R. Sukthankar Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization K. Saenko, T. Darrell Unsupervised Learning of Visual Sense Models for Polysemous Words K. Yu, W. Xu, Y. Gong Deep Learning with Kernel Regularization for Visual Recognition I. Murray, R. Salakhutdinov Evaluating probabilities under high-dimensional latent variable models
8:45pm - 12:00am	Posters
	S. Cohen, K. Gimpel, N. Smith Unsupervised Bayesian Parameter Estimation for Probabilistic Grammars D. Downey, O. Etzioni Analyzing the Monotonic Feature Abstraction for Text Classification J. Boyd-Graber, D. Blei Syntactic Topic Models L. Yang, R. Jin, R. Sukthankar Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization M. Dudik, S. Phillips Generative and Discriminative Learning with Unknown Labeling Bias K. Weinberger, O. Chapelle Large Margin Taxonomy Embedding for Document Categorization M. Blaschko, A. Gretton Learning Taxonomies by Dependence Maximization J. Huang, B. Frey Structured ranking learning using cumulative distribution networks S. Clémençon, N. Vayatis Overlaying classifiers: a practical approach for optimal ranking S. Goel, J. Langford, A. Strehl Predictive Indexing for Fast Search R. Tillman, D. Danks, C. Glymour Integrating Locally Learned Causal Structures with Overlapping Variables J. Pellet, A. Elisseeff Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets G. Schweikert, C. Widmer, B. Schölkopf, G. Raetsch An empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis A. Bouchard-Côté, M. Jordan, D. Klein Efficient Inference in Phylogenetic InDel Trees D. Bagnell, D. Bradley (Not) Sparse Coding C. Shen, A. Welsh, L. Wang PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning T. Zhang Multi-stage Convex Relaxation for Learning with Sparse Regularization P. Rai, H. Daume III Nonparametric Bayesian Sparse Hierarchical Factor Modeling and Regression S. Haufe, V. Nikulin, A. Ziehe, K. Muller, G. Nolte Estimating vector fields using sparse basis field expansions I. Steinwart, A. Christmann Sparsity of SVMs that use the epsilon-insensitive loss P. Ravikumar, G. Raskutti, M. Wainwright, B. Yu Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \ell_1-regularizedMLE N. Komodakis, N. Paragios, G. Tziritas Clustering via LP-based Stabilities S. Ben-David, M. Ackerman Measures of Clustering Quality: A Working Set of Axioms for Clustering O. Shamir, N. Tishby On the Reliability of Clustering Stability in the Large Sample Regime L. Huang, D. Yan, M. Jordan, N. Taft Spectral Clustering with Perturbed Data M. Maier, U. von Luxburg, M. Hein Influence of graph construction on graph-based clustering measures V. Sindhwani, J. Hu, A. Mojsilovic Regularized Co-Clustering with Dual Supervision D. Zhao, X. Tang Cyclizing Clusters via Zeta Function of a Graph D. Gorur, Y. Teh An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering Y. Weiss, A. Torralba, R. Fergus Spectral Hashing P. Li, K. Church, T. Hastie One sketch for all: Theory and Application of Conditional Random Sampling Z. Hussain, J. Shawe-Taylor Theory of matching pursuit M. Mohri, A. Rostamizadeh Rademacher Complexity Bounds for Non-I.I.D. Processes S. Kakade, K. Sridharan, A. Tewari On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization M. Shah Risk Bounds for Randomized Sample Compressed Classifiers T. Kanamori, S. Hido, M. Sugiyama Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection P. Garrigues, L. El Ghaoui An Homotopy Algorithm for the Lasso with Online Observations Y. Guo Supervised Exponential Family Principal Component Analysis via Convex Optimizatio A. Smith, X. Huo, H. Zha Convergence and Rate of Convergence of A Manifold-Based Dimension Reduction C. Walder, B. Schölkopf Diffeomorphic Dimensionality Reduction S. Bickel, C. Sawade, T. Scheffer Transfer Learning by Distribution Matching for Targeted Advertising I. Mukherjee, D. Blei Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation K. Saenko, T. Darrell Unsupervised Learning of Visual Sense Models for Polysemous Words T. Minka, J. Winn Gates D. Agarwal, L. Zhang Fast Computation of Posterior Mode in Multi-Level Hierarchical Models I. Murray, R. Salakhutdinov Evaluating probabilities under high-dimensional latent variable models L. Kroc, A. Sabharwal, B. Selman Counting Solution Clusters Using Belief Propagation D. Lee, A. Gray Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method Z. Harchaoui, F. Bach, E. Moulines Kernel Change-point Analysis K. Yu, W. Xu, Y. Gong Deep Learning with Kernel Regularization for Visual Recognition V. Nair, G. Hinton Implicit Mixtures of Restricted Boltzmann Machines F. Perez-Cruz Estimation of Information Theoretic Measures for Continuous Random Variables K. Chaudhuri, C. Monteleoni Privacy-preserving logistic regression J. McAuley, T. Caetano, A. Smola Robust Near-Isometric Matching via Structured Learning of Graphical Models G. Heitz, G. Elidan, B. Packer, D. Koller LOOPS: Localizing Object Outlines using Probabilistic Shape J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman SDL: Supervised Dictionary Learning A. Gupta, J. Shi, L. Davis A "Shape Aware" Model for semi-supervised Learning of Objects and its Context L. Latecki, C. Lu, M. Sobel, X. Bai Multiscale Random Fields with Application to Contour Grouping J. Le Roux, A. de Cheveigné, L. Parra Adaptive Template Matching with Shift-Invariant Semi-NMF Z. Lu, T. Leen, J. Kaye Hierarchical Fisher Kernels for Longitudinal Data B. Calderhead, M. Girolami, N. Lawrence Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes T. Tran, D. Phung, H. Bui, S. Venkatesh Hierarchical Conditional Random Fields for Recursive Sequential Data J. Robinson, A. Hartemink Non-stationary dynamic Bayesian networks D. Nguyen-Tuong, M. Seeger, J. Peters Local Gaussian Process Regression for Real Time Online Model Learning M. Herbster, M. Pontil, G. Lever On-Line Prediction on Large Diameter Graphs F. Radlinski, D. Chakrabarti, R. Kumar, E. Upfal Mortal Multi-Armed Bandits M. Petrik, B. Scherrer Biasing Approximate Dynamic Programming with a Lower Discount Factor P. Coquelin, R. Deguest, R. Munos Particle Filter-based Policy Gradient in POMDPs M. Milani Fard, J. Pineau MDPs with Non-Deterministic Policies R. Sutton, C. Szepesvari, H. Maei A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approxi D. Precup, J. Taylor, P. Panangaden Bounding Performance Loss in Approximate MDP Homomorphisms O. Simsek, A. Barto Skill Characterization Based on Betweenness D. Ray, B. King-Casas, P. Montague, P. Dayan Bayesian Model of Behaviour in Economic Games D. Di Castro, D. Volkinshtein, R. Meir Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation C. Kolodziejski, B. Porr, M. Tamosiunaite, F. Woergoetter On the equivalence between TD learning and differential Hebbian learning using a local third factor C. Kemp, F. Xu An ideal observer model of infant object perception J. Reynolds, M. Mozer Temporal Dynamics of Cognitive Control T. Griffiths, C. Lucas, J. Williams, M. Kalish Modeling human function learning with Gaussian processes T. Schmah, G. Hinton, R. Zemel Competing RBM density models for classification of fMRI images P. Xu, T. Horiuchi, P. Abshire Short-Term Depression in VLSI Stochastic Synapse M. Grosse-Wentrup Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing C. Fung, K. Wong, S. Wu Tracking Changing Stimuli in Continuous Attractor Neural Networks J. Lewi, R. Butera, L. Paninski Designing neurophysiology experiments to optimally constrain receptive field models along parametric B. Nessler, M. Pfeiffer, W. Maass Hebbian Learning of Bayes Optimal Decisions M. Botvinick, J. An Goal-directed decision making in prefrontal cortex: a computational framework B. Yu, J. Cunningham, G. Santhanam, S. Ryu, K. Shenoy, M. Sahani Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity V. Gómez, A. Kaltenbrunner, V. López, H. Kappen Self-organization using dynamical synapses A. Ponzi, J. Wickens Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons J. Huo, Z. Yang, A. Murray Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl T. Sandler, J. Blitzer, P. Talukdar, L. Ungar Regularized Learning with Networks of Features
Tuesday
8:30 - 9:50am	Oral session 2: Sensorimotor ControlSession Chair:Arthur Gretton
	Daniel Wolpert Computations in Human Sensorimotor Control L. Shpigelman, H. Lalazar, E. Vaadia Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control
9:50 - 10:00am	Spotlights
	A. Haith, C. Jackson, R. Miall, S. Vijayakumar Unifying the Sensory and Motor Components of Sensorimotor Adaptation J. Hill, J. Farquhar, S. Martens, F. Bießmann, B. Schölkopf Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance M. Seeger, H. Nickisch, R. Pohmann, B. Schölkopf Bayesian Experimental Design of Magnetic Resonance Imaging Sequences J. Xu, T. Griffiths How memory biases affect information transmission: A rational analysis of serial reproduction C. Lucas, T. Griffiths, F. Xu, C. Fawcett A rational model of preference learning and choice prediction by children M. Jones, M. Mozer, S. Kinoshita Optimal Response Initiation: Why Recent Experience Matters J. Austerweil, T. Griffiths Analyzing human feature learning as nonparametric Bayesian inference H. Graf, H. Cadambi, I. Durdanovic, V. Jakkula, M. Sankaradass, E. Cosatto, S. Chakradhar A Massively Parallel Digital Learning Processor P. Frasconi, A. Passerini Predicting the Geometry of Metal Binding Sites from Protein Sequence
10:00 - 10:30am	Break
10:30 - 11:50am	Oral session 3: Learning from Reinforcement: Modeling and ControlSession Chair:Michael Bowling
	G. Luksys, C. Sandi, W. Gerstner Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning M. Todd, Y. Niv, J. Cohen Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement E. Talvitie, S. Singh Simple Local Models for Complex Dynamical Systems J. Kober, J. Peters Policy Search for Motor Primitives in Robotics
11:50am - 12:00pm	Spotlights
	K. Chai, C. Williams, S. Klanke, S. Vijayakumar Multi-task Gaussian Process Learning of Robot Inverse Dynamics A. Nouri, M. Littman Multi-resolution Exploration in Continuous Spaces L. Zettlemoyer, B. Milch, L. Kaelbling Multi-Agent Filtering with Infinitely Nested Beliefs G. Neumann, J. Peters Fitted Q-iteration by Advantage Weighted Regression J. Roberts, R. Tedrake Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms P. Ruvolo, I. Fasel, j. movellan Optimization on a Budget: A Reinforcement Learning Approach P. Auer, T. Jaksch, R. Ortner Near-optimal Regret Bounds for Reinforcement Learning Y. Wang, J. Audibert, R. Munos Algorithms for Infinitely Many-Armed Bandits S. Shalev-Shwartz, S. Kakade Mind the Duality Gap: Logarithmic regret algorithms for online optimization M. Streeter, D. Golovin An Online Algorithm for Maximizing Submodular Functions
12:00 - 2:00pm	Lunch
2:00 - 3:20pm	Oral session 4: Combinatorial ApproximationSession Chair:Erik Sudderth
	Pascal van Hentenryck Online Stochastic Combinatorial Optimization Y. Wexler, C. Meek MAS: a multiplicative approximation scheme for probabilistic inference
3:20 - 3:30pm	Spotlights
	D. Sontag, A. Globerson, T. Jaakkola Clusters and Coarse Partitions in LP Relaxations P. Mudigonda, P. Torr Improved Moves for Truncated Convex Models G. Elidan, S. Gould Learning Bounded Treewidth Bayesian Networks B. Yackley, E. Corona, T. Lane Bayesian Network Score Approximation using a Metagraph Kernel M. Raginsky, S. Lazebnik, R. Willett, J. Silva Near-minimax recursive density estimation on the binary hypercube J. Mooij, H. Kappen Bounds on marginal probability distributions Z. Zhang, M. Jordan, D. Yeung Posterior Consistency of the Silverman g-prior in Bayesian Model Choice M. Opper, U. Paquet, O. Winther Improving on Expectation Propagation R. Adams, I. Murray, D. MacKay The Gaussian Process Density Sampler M. Titsias, N. Lawrence, M. Rattray Efficient Sampling for Gaussian Process Inference using Control Variables
3:30 - 4:00pm	Break
4:00 - 5:20pm	Oral session 5: Fast Output Processing, Novelty Detection and Unlabeled DataSession Chair:Paolo Frasconi
	P. Jain, B. Kulis, I. Dhillon, K. Grauman Online Metric Learning and Fast Similarity Search M. Herbster, M. Pontil, S. Rojas Galeano Fast Prediction on a Tree D. Weinshall, H. Hermansky, A. Zweig, J. Luo, H. Jimison, F. Ohl, M. Pavel Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree A. Singh, R. Nowak, X. Zhu Unlabeled data: Now it helps, now it doesn't
5:20 - 5:30pm	Spotlights
	M. Amini, N. Usunier, F. Laviolette A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning H. Masnadi-Shirazi, N. Vasconcelos On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost P. Long, R. Servedio Adaptive Martingale Boosting S. Kakade, A. Tewari On the Generalization Ability of Online Strongly Convex Programming Algorithms A. Rahimi, B. Recht Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning J. Langford, L. Li, T. Zhang Sparse Online Learning via Truncated Gradient R. Nock, F. NIELSEN On the Efficient Minimization of Classification Calibrated Surrogates K. Crammer, M. Dredze, F. Pereira Exact Convex Confidence-Weighted Learning J. Tam, J. Simsa, S. Hyde, L. von Ahn Breaking Audio CAPTCHAs with Machine Learning Techniques P. Hoyer, D. Janzing, J. Mooij, J. Peters, B. Schölkopf Nonlinear causal discovery with additive noise models A. Yu, J. Cohen Sequential effects: Superstition or rational behavior?
6:00 - 8:00pm	Dinner
7:30pm - 12:00am	Demonstrations
	J. Conradt, P. Lichtsteiner, R. Berner, T. Delbruck, R. Douglas, M. Cook A Pencil Balancing Robot Using Only Spike-based Visual Input S. Gould, M. Quigley, S. Batra, E. Klingbiel, Q. Le, A. Ng High-Accuracy 3D Sensing for Mobile Manipulators D. George, J. Edwards, J. Niemasik, R. Marianetti, B. Saphir, S. Ahmad Vision Toolkit Based on Hierarchical Temporal Memory C. Grozea, S. Fazli, M. Danoczy, F. Popescu Play Brain-Pong in 10 Minutes N. de Freitas, A. Davar Worio: A Web-Scale Machine Learning System A. Gray MLPACK: Scalable Machine Learning Software
7:30pm - 12:00am	Posters
	A. Farahmand, M. Ghavamzadeh, C. Szepesvari, S. Mannor Regularized Policy Iteration P. Auer, T. Jaksch, R. Ortner Near-optimal Regret Bounds for Reinforcement Learning G. Neumann, J. Peters Fitted Q-iteration by Advantage Weighted Regression J. Roberts, R. Tedrake Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms J. Kober, J. Peters Policy Search for Motor Primitives in Robotics E. Talvitie, S. Singh Simple Local Models for Complex Dynamical Systems K. Chai, C. Williams, S. Klanke, S. Vijayakumar Multi-task Gaussian Process Learning of Robot Inverse Dynamics Y. Wang, J. Audibert, R. Munos Algorithms for Infinitely Many-Armed Bandits A. Nouri, M. Littman Multi-resolution Exploration in Continuous Spaces L. Zettlemoyer, B. Milch, L. Kaelbling Multi-Agent Filtering with Infinitely Nested Beliefs A. Haith, C. Jackson, R. Miall, S. Vijayakumar Unifying the Sensory and Motor Components of Sensorimotor Adaptation I. Sutskever, G. Hinton, G. Taylor The Recurrent Temporal Restricted Boltzmann Machine P. Ruvolo, I. Fasel, j. movellan Optimization on a Budget: A Reinforcement Learning Approach M. Streeter, D. Golovin An Online Algorithm for Maximizing Submodular Functions P. Jain, B. Kulis, I. Dhillon, K. Grauman Online Metric Learning and Fast Similarity Search M. Herbster, M. Pontil, S. Rojas Galeano Fast Prediction on a Tree Y. Tam, T. Schultz Correlated Bigram LSA for Unsupervised Language Model Adaptation Y. Zhang, J. Schneider, A. Dubrawski Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text A. Mnih, G. Hinton A Scalable Hierarchical Distributed Language Model O. Chapelle, C. Do, Q. Le, A. Smola, C. Teo Tighter Bounds for Structured Estimation D. Weinshall, H. Hermansky, A. Zweig, J. Luo, H. Jimison, F. Ohl, M. Pavel Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree A. Singh, R. Nowak, X. Zhu Unlabeled data: Now it helps, now it doesn't J. Tam, J. Simsa, S. Hyde, L. von Ahn Breaking Audio CAPTCHAs with Machine Learning Techniques M. Amini, N. Usunier, F. Laviolette A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning R. Nock, F. NIELSEN On the Efficient Minimization of Classification Calibrated Surrogates K. Crammer, M. Dredze, F. Pereira Exact Convex Confidence-Weighted Learning Z. Xu, R. Jin, I. King, M. Lyu An Extended Level Method for Efficient Multiple Kernel Learning G. Elidan, S. Gould Learning Bounded Treewidth Bayesian Networks B. Yackley, E. Corona, T. Lane Bayesian Network Score Approximation using a Metagraph Kernel J. Zhu, E. Xing, B. Zhang Partially Observed Maximum Entropy Discrimination Markov Networks M. Raginsky, S. Lazebnik, R. Willett, J. Silva Near-minimax recursive density estimation on the binary hypercube Y. Grandvalet, J. Keshet, A. Rakotomamonjy, S. Canu Suppport Vector Machines with a Reject Option J. Langford, L. Li, T. Zhang Sparse Online Learning via Truncated Gradient S. Kakade, A. Tewari On the Generalization Ability of Online Strongly Convex Programming Algorithms A. Rahimi, B. Recht Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning H. Masnadi-Shirazi, N. Vasconcelos On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost G. Cavallanti, N. Cesa-Bianchi, C. Gentile Linear Classification and Selective Sampling Under Low Noise Conditions O. Dekel From Online to Batch Learning with Cutoff-Averaging P. Long, R. Servedio Adaptive Martingale Boosting S. Shalev-Shwartz, S. Kakade Mind the Duality Gap: Logarithmic regret algorithms for online optimization P. Bertail, S. Clémençon, N. Vayatis On Bootstrapping the ROC Curve S. Lacoste-Julien, F. Sha, M. Jordan DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification Z. Zhang, M. Jordan, D. Yeung Posterior Consistency of the Silverman g-prior in Bayesian Model Choice Y. Lin, T. Liu, C. Fuh Dimensionality Reduction for Data in Multiple Feature Representations V. Jain, H. Seung Natural Image Denoising with Convolutional Networks A. Fletcher, S. Rangan, V. Goyal Resolution Limits of Sparse Coding in High Dimensions N. Schraudolph, D. Kamenetsky Efficient Exact Inference in Planar Ising Models M. Opper, U. Paquet, O. Winther Improving on Expectation Propagation N. Ailon Reconciling Real Scores with Binary Comparisons: A Unified Logistic Model for Ranking M. Titsias, N. Lawrence, M. Rattray Efficient Sampling for Gaussian Process Inference using Control Variables Y. Wexler, C. Meek MAS: a multiplicative approximation scheme for probabilistic inference R. Adams, I. Murray, D. MacKay The Gaussian Process Density Sampler M. Seeger, H. Nickisch, R. Pohmann, B. Schölkopf Bayesian Experimental Design of Magnetic Resonance Imaging Sequences J. Mooij, H. Kappen Bounds on marginal probability distributions D. Sontag, A. Globerson, T. Jaakkola Clusters and Coarse Partitions in LP Relaxations T. Kim, R. Cipolla MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features X. He, R. Zemel Learning Hybrid Models for Image Annotation with Partially Labeled Data P. Srinivasan, L. Wang, J. Shi Grouping Contours Via a Related Image P. Mudigonda, P. Torr Improved Moves for Truncated Convex Models F. Bach Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning P. Hoyer, D. Janzing, J. Mooij, J. Peters, B. Schölkopf Nonlinear causal discovery with additive noise models P. Frasconi, A. Passerini Predicting the Geometry of Metal Binding Sites from Protein Sequence G. Quon, Y. Teh, E. Chan, M. Brudno, T. Hughes, Q. Morris A mixture model for the evolution of gene expression in non-homogeneous datasets N. Aleks, S. Russell, M. Madden, D. Morabito, G. Manley, K. Staudenmayer, M. Cohen Probabilistic detection of short events, with application to critical care monitoring L. Shpigelman, H. Lalazar, E. Vaadia Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control M. Tangermann (ne Schröder), M. Krauledat, K. Grzeska, M. Sagebaum, B. Blankertz, K. Muller Playing Pinball with non-invasive BCI H. Graf, H. Cadambi, I. Durdanovic, V. Jakkula, M. Sankaradass, E. Cosatto, S. Chakradhar A Massively Parallel Digital Learning Processor J. Hill, J. Farquhar, S. Martens, F. Bießmann, B. Schölkopf Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance J. Austerweil, T. Griffiths Analyzing human feature learning as nonparametric Bayesian inference G. Luksys, C. Sandi, W. Gerstner Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning K. Katahira, J. Nishikawa, K. Okanoya, M. Okada A Bayesian Approach for Extracting State Transition Dynamics from Multiple Spike Trains D. Acuna, P. Schrater Structure Learning in Human Sequential Decision-Making J. Gasthaus, F. Wood, D. Gorur, Y. Teh Dependent Dirichlet Process Spike Sorting M. Jones, M. Mozer, S. Kinoshita Optimal Response Initiation: Why Recent Experience Matters J. Xu, T. Griffiths How memory biases affect information transmission: A rational analysis of serial reproduction A. Yu, J. Cohen Sequential effects: Superstition or rational behavior? C. Lucas, T. Griffiths, F. Xu, C. Fawcett A rational model of preference learning and choice prediction by children M. Todd, Y. Niv, J. Cohen Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement K. Wimmer, M. Stimberg, R. Martin, L. Schwabe, J. Mariño, J. Schummers, D. Lyon, M. Sur, K. Obermayer Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 Q. Huys, j. vogelstein, P. Dayan Depression: an RL formulation and a behavioural test
Wednesday
8:30 - 9:50am	Oral session 6: Neural CodingSession Chair:Koby Crammer
	H. Sebastian Seung Connectome: the quest to deconstruct the brain A. Onken, S. Grünewälder, M. Munk, K. Obermayer Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex
9:50 - 10:00am	Spotlights
	P. Berkes, F. Wood, J. Pillow Characterizing neural dependencies with Poisson copula models M. Oizumi, T. Ishii, K. Ishibashi, T. Hosoya, M. Okada A general framework for investigating how far the decoding process in the brain can be simplified D. Wipf, J. Owen, H. Attias, K. Sekihara, S. Nagarajan Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, J. Gallant Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images M. Muezzinoglu, A. Vergara, R. Huerta, T. Nowotny, N. Rulkov, H. Abarbanel, A. Selverston, M. Rabinovich Artificial Olfactory Brain for Mixture Identification Z. Yang, W. Liu An Algorithm for Microchip Spike Sorting F. Sinz, M. Bethge The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction R. Haefner, B. Cumming An improved estimator of Variance Explained in the presence of noise D. Endres, P. Foldiak Interpreting the neural code with Formal Concept Analysis X. Hou, L. Zhang Dynamic Visual Attention: Searching for coding length increments
10:00 - 10:30am	Break
10:30 - 11:50am	Oral session 7: Complex Dynamical Systems: Modeling and EstimationSession Chair:David Fleet
	R. Levy, F. Reali, T. Griffiths Modeling the effects of memory on human online sentence processing with particle filters B. Schrauwen, L. Buesing, R. Legenstein On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing I. Akhter, Y. Sheikh, S. Khan, T. Kanade Nonrigid Structure from Motion in Trajectory Space A. Yuille, S. Wu, H. Lu Model selection and velocity estimation using novel priors for motion patterns
11:50am - 12:00pm	Spotlights
	A. Graves, J. Schmidhuber Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks L. Zhu, Y. Chen, Y. Lin, A. Yuille A Hierarchical Image Model for Polynomial-Time 2D Parsing Y. Wang, G. Mori Learning a discriminative hidden part model for human action recognition C. Cadieu, B. Olshausen Learning Transformational Invariants from Time-Varying Natural Images E. Fox, E. Sudderth, M. Jordan, A. Willsky Nonparametric Bayesian Learning of Switching Linear Dynamical Systems J. Van Gael, Y. Teh, Z. Ghahramani The Infinite Factorial Hidden Markov Model E. Airoldi, D. Blei, S. Fienberg, E. Xing Mixed Membership Stochastic Blockmodels Y. Yamanishi Supervised Bipartite Graph Inference S. Zhu, K. Yu, Y. Gong Stochastic Relational Models for Large-scale Dyadic Data using MCMC I. Sutskever, G. Hinton Using matrices to model symbolic relationship
12:00 - 2:00pm	Lunch
2:00 - 3:20pm	Oral session 8: Physics and High Order StatisticsSession Chair:Tony Jebara
	Harrison Prosper Machine Learning in High Energy Physics K. Fukumizu, B. Sriperumbudur, A. Gretton, B. Schölkopf Characteristic Kernels on Groups and Semigroups
3:20 - 3:30pm	Spotlights
	X. Zhang, L. Song, A. Gretton, A. Smola Kernel Measures of Independence for non-iid Data S. Ji, L. Sun, R. Jin, J. Ye Multi-label Multiple Kernel Learning P. Kuksa, P. Huang, V. Pavlovic Scalable Algorithms for String Kernels with Inexact Matching N. Quadrianto, L. Song, A. Smola Kernelized Sorting H. Yang, I. King, M. Lyu Learning with Consistency between Inductive Functions and Kernels J. Kim, C. Scott Performance analysis for L_2 kernel classification L. Jacob, F. Bach, J. Vert Clustered Multi-Task Learning: A Convex Formulation Y. Mansour, M. Mohri, A. Rostamizadeh Domain Adaptation with Multiple Sources S. Negahban, M. Wainwright Phase transitions for high-dimensional joint support recovery W. Dai, Y. Chen, G. Xue, Q. Yang, Y. Yu Translated Learning
3:30 - 4:00pm	Break
4:00 - 5:20pm	Oral session 9: Sparse Learning and RankingSession Chair:Jean-Yves Audibert
	T. Zhang Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models P. Carbonetto, M. Schmidt, N. de Freitas An interior-point stochastic approximation method and an L1-regularized delta rule T. Qin, T. Liu, X. Zhang, D. Wang, H. Li Global Ranking Using Continuous Conditional Random Fields S. Jagabathula, D. Shah Inferring rankings under constrained sensing
5:20 - 5:30pm	Spotlights
	H. Liu, J. Lafferty, L. Wasserman Nonparametric regression and classification with joint sparsity constraints H. Xu, C. Caramanis, S. Mannor Robust Regression and Lasso G. Obozinski, M. Wainwright, M. Jordan High-dimensional union support recovery in multivariate regression V. Cevher, M. Duarte, C. Hegde, R. Baraniuk Sparse Signal Recovery Using Markov Random Fields C. Archambeau, F. Bach Sparse probabilistic projections L. Mackey Deflation Methods for Sparse PCA M. Nguyen, F. De la Torre Robust Kernel Principal Component Analysis S. Mohamed, K. Heller, Z. Ghahramani Bayesian Exponential Family PCA L. Faivishevsky, J. Goldberger ICA based on a Smooth Estimation of the Differential Entropy Q. Wu, S. Mukherjee, F. Liang Localized Sliced Inverse Regression
6:00 - 8:00pm	Dinner
7:30pm - 12:00am	Demonstrations
	L. van der Maaten, G. Hinton Visualizing NIPS Cooperations using Multiple Maps t-SNE K. Eng, T. Delbruck, M. Schrag, M. Boerlin Real-time Topology Learning T. Minka, J. Winn, J. Guiver, A. Kannan Infer.NET: Software for Graphical Models B. Tanner, A. White, R. Sutton RL-Glue: From Grid Worlds to Sensor Rich Robots D. Touretzky, E. Tira-Thompson, G. Sato, D. Rice The Chiara: A New Robotic Platform for Education and Research P. Ruvolo, M. Bartlett, N. Butko, C. Lainscsek, G. Littlewort, J. Whitehill, T. Wu, j. movellan Machine Perception for Human Machine Interaction
7:30pm - 12:00am	Posters
	Z. Yang, W. Liu An Algorithm for Microchip Spike Sorting A. Onken, S. Grünewälder, M. Munk, K. Obermayer Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex B. Schrauwen, L. Buesing, R. Legenstein On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing M. Oizumi, T. Ishii, K. Ishibashi, T. Hosoya, M. Okada A general framework for investigating how far the decoding process in the brain can be simplified P. Berkes, F. Wood, J. Pillow Characterizing neural dependencies with Poisson copula models R. Haefner, B. Cumming An improved estimator of Variance Explained in the presence of noise F. Sinz, M. Bethge The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction D. Endres, P. Foldiak Interpreting the neural code with Formal Concept Analysis M. Muezzinoglu, A. Vergara, R. Huerta, T. Nowotny, N. Rulkov, H. Abarbanel, A. Selverston, M. Rabinovich Artificial Olfactory Brain for Mixture Identification D. Wipf, J. Owen, H. Attias, K. Sekihara, S. Nagarajan Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG E. Ludvig, R. Sutton, E. Verbeek, J. Kehoe A computational model of hippocampal function in trace conditioning R. Natarajan, I. Murray, L. Shams, R. Zemel Comparing model predictions of response bias and variance in cue combination P. Dayan Load and Attentional Bayes X. Zhu, R. Castro, T. Rogers, R. Nowak, R. Qian, C. Kalish Human Active Learning R. Levy, F. Reali, T. Griffiths Modeling the effects of memory on human online sentence processing with particle filters A. Braunstein, Z. Wei, S. Jensen, J. McAuliffe A spatially varying two-sample recombinant coalescent, with applications to HIV escape response T. Qin, T. Liu, X. Zhang, D. Wang, H. Li Global Ranking Using Continuous Conditional Random Fields P. Blunsom, T. Cohn, M. Osborne Bayesian Synchronous Grammar Induction K. Collins-Thompson Estimating Robust Query Models with Convex Optimization D. Agarwal, B. Chen, P. Elango, N. Motgi, S. Park, R. Ramakrishnan, S. Roy, J. Zachariah Online Models for Content Optimization S. Ji, L. Sun, R. Jin, J. Ye Multi-label Multiple Kernel Learning Y. Yamanishi Supervised Bipartite Graph Inference P. Kuksa, P. Huang, V. Pavlovic Scalable Algorithms for String Kernels with Inexact Matching S. Jagabathula, D. Shah Inferring rankings under constrained sensing G. Obozinski, M. Wainwright, M. Jordan High-dimensional union support recovery in multivariate regression H. Liu, J. Lafferty, L. Wasserman Nonparametric regression and classification with joint sparsity constraints H. Xu, C. Caramanis, S. Mannor Robust Regression and Lasso P. Carbonetto, M. Schmidt, N. de Freitas An interior-point stochastic approximation method and an L1-regularized delta rule F. Steinke, M. Hein Non-parametric Regression Between Manifolds S. Negahban, M. Wainwright Phase transitions for high-dimensional joint support recovery Y. Mansour, M. Mohri, A. Rostamizadeh Domain Adaptation with Multiple Sources P. Shivaswamy, T. Jebara Relative Margin Machines L. Jacob, F. Bach, J. Vert Clustered Multi-Task Learning: A Convex Formulation K. Fukumizu, B. Sriperumbudur, A. Gretton, B. Schölkopf Characteristic Kernels on Groups and Semigroups Q. Wu, S. Mukherjee, F. Liang Localized Sliced Inverse Regression J. Kim, C. Scott Performance analysis for L_2 kernel classification T. Zhang Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models S. Clémençon, N. Vayatis Empirical performance maximization for linear rank statistics X. Zhang, L. Song, A. Gretton, A. Smola Kernel Measures of Independence for non-iid Data K. Sridharan, S. Shalev-Shwartz, N. Srebro Fast Rates for Regularized Objectives H. Yang, I. King, M. Lyu Learning with Consistency between Inductive Functions and Kernels W. Dai, Y. Chen, G. Xue, Q. Yang, Y. Yu Translated Learning L. Faivishevsky, J. Goldberger ICA based on a Smooth Estimation of the Differential Entropy M. Nguyen, F. De la Torre Robust Kernel Principal Component Analysis S. Mohamed, K. Heller, Z. Ghahramani Bayesian Exponential Family PCA L. Mackey Deflation Methods for Sparse PCA C. Archambeau, F. Bach Sparse probabilistic projections N. Quadrianto, L. Song, A. Smola Kernelized Sorting M. Holmes, A. Gray, C. Isbell QUIC-SVD: Fast SVD Using Cosine Trees M. Isard, J. MacCormick, K. Achan Continuously-adaptive discretization for message-passing algorithms C. Yuan, C. Neubauer Variational Mixture of Gaussian Process Experts L. El Ghaoui, A. Gueye A Convex Upper Bound on the Log-Partition Function E. Airoldi, D. Blei, S. Fienberg, E. Xing Mixed Membership Stochastic Blockmodels S. Zhu, K. Yu, Y. Gong Stochastic Relational Models for Large-scale Dyadic Data using MCMC D. Roy, Y. Teh The Mondrian Process A. Asuncion, P. Smyth, M. Welling Asynchronous Distributed Learning of Topic Models S. Bubeck, R. Munos, G. Stoltz, C. Szepesvari Online Optimization in X-Armed Bandits J. Ting, M. Kalakrishnan, S. Vijayakumar, S. Schaal Bayesian Kernel Shaping for Learning Control E. Fox, E. Sudderth, M. Jordan, A. Willsky Nonparametric Bayesian Learning of Switching Linear Dynamical Systems S. Das, M. Magdon-Ismail Adapting to a Market Shock: Optimal Sequential Market-Making V. Morariu, B. Srinivasan, V. Raykar, R. Duraiswami, L. Davis Automatic online tuning for fast Gaussian summation M. Alvarez, N. Lawrence Sparse Convolved Gaussian Processes for Multi-ouptut Regression J. Van Gael, Y. Teh, Z. Ghahramani The Infinite Factorial Hidden Markov Model I. Sutskever, G. Hinton Using matrices to model symbolic relationship G. Cao, C. Bouman Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform G. Heitz, S. Gould, A. Saxena, D. Koller Cascaded Classification Models: Combining Models for Holistic Scene Understanding S. Vijayanarasimhan, K. Grauman Multi-Level Active Prediction of Useful Image Annotations for Recognition I. Akhter, Y. Sheikh, S. Khan, T. Kanade Nonrigid Structure from Motion in Trajectory Space L. Zhu, Y. Chen, Y. Lin, A. Yuille A Hierarchical Image Model for Polynomial-Time 2D Parsing Y. Wang, G. Mori Learning a discriminative hidden part model for human action recognition V. Cevher, M. Duarte, C. Hegde, R. Baraniuk Sparse Signal Recovery Using Markov Random Fields J. Hamm, D. Lee Extended Grassmann Kernels for Subspace-Based Learning C. Cadieu, B. Olshausen Learning Transformational Invariants from Time-Varying Natural Images E. Sudderth, M. Jordan Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes A. Yuille, S. Wu, H. Lu Model selection and velocity estimation using novel priors for motion patterns S. Chiappa, J. Kober, J. Peters Using Bayesian Dynamical Systems for Motion Template Libraries X. Hou, L. Zhang Dynamic Visual Attention: Searching for coding length increments A. Graves, J. Schmidhuber Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, J. Gallant Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images S. Lyu, E. Simoncelli Reducing statistical dependencies in natural signals using radial Gaussianization
Thursday
8:30 - 10:10am	Oral session 10: Nonparametric Processes, Scene Processing and Image StatisticsSession Chair:Max Welling
	D. Roy, Y. Teh The Mondrian Process E. Sudderth, M. Jordan Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes G. Heitz, S. Gould, A. Saxena, D. Koller Cascaded Classification Models: Combining Models for Holistic Scene Understanding S. Vijayanarasimhan, K. Grauman Multi-Level Active Prediction of Useful Image Annotations for Recognition S. Lyu, E. Simoncelli Reducing statistical dependencies in natural signals using radial Gaussianization
10:10 - 10:40am	Break
10:40am - 12:00pm	Oral session 11: Attention and MindSession Chair:Aaron Courville
	P. Dayan Load and Attentional Bayes Rebecca Saxe Theory of Mind with fMRI
12:00 - 1:00pm	Lunch
1:30 - 4:30pm	Mini Symposia
	R. Kondor, G. Lebanon, J. Morton Algebraic methods in machine learning B. Freeman, B. Schölkopf Computational Photography G. Chechik, C. Leslie, Q. Morris, W. Noble, G. Raetsch Machine Learning in Computational Biology D. Polani, N. Tishby Principled Theoretical Frameworks for the Perception-Action Cycle

The schedule was last modified on 2008-12-12 07:14 PST