NIPS : Conferences : 2006 : Program

Schedule

Conference Sessions (December 4-7, 2006)

Monday
6:30 - 8:30pm	Opening Banquet
	J. Bennett The Netflix Prize
7:30pm - 12:00am	Demonstrations
	Y. Ivanov, J. Westhues, D. Leigh, C. Wren, A. Sorokin, I. Kaur Ambient Intelligence for Better Buildings K. Bonawitz, V. Mansinghka Blaise: A System for Interactive Development of High Performance Inference Algorithms D. Verstraeten, B. Schrauwen Hardware speech recognition using Reservoir Computing J. Arenas-García, L. Hansen, T. Lehn-Schioeler, K. Petersen, J. Larsen MIROCKET O. Teytaud, S. Gelly MoGo: exploration-exploitation in Monte-Carlo Go using UCT and patterns D. Alleysson, A. Benoit, B. Durette, J. Herault Real-time bio-inspired retina simulation software with non-linear, adaptive and chromatic spatio-temporal processing S. Sonnenburg, G. Raetsch SHOGUN Machine Learning Toolbox P. Lichtsteine, T. Delbruck Using an event-based silicon retina for fast sensory motor processing
7:30pm - 12:00am	Poster Session
	Y. Teh, D. Newman, M. Welling A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation P. Bartlett, M. Traskin AdaBoost is Consistent J. Kimmel, R. Salter, P. Thomas An Information Theoretic Framework for Eukaryotic Gradient Sensing W. Kienzle, F. Wichmann, B. Schölkopf, M. Franz A Nonparametric Approach to Bottom-Up Visual Saliency D. Navarro, T. Griffiths A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments J. Zumer, H. Attias, K. Sekihara, S. Nagarajan A Probabilistic Algorithm Integrating Source Localization and Noise Suppression for MEG and EEG data A. Vedaldi A Rate-Distortion Approach to Joint Pattern Alignment E. Even-Dar, M. Kearns A Small World Threshold for Economic Network Formation Y. Wang, R. Douglas, S. Liu Attentional Processing on a Spike-Based VLSI Neural Network P. Long, R. Servedio Attribute-efficient learning of linear threshold functions under unconcentrated distributions L. Charlin, P. Poupart, R. Shioda Automated Hierarchy Discovery for Planning in Partially Observable Domains T. Cour, P. Srinivasan, J. Shi Balanced Graph Matching A. Levin Blind Motion Deblurring Using Image Statistics O. Chapelle, V. Sindhwani, S. Selvaraj Keerthi Branch and Bound for Semi-Supervised Support Vector Machines K. Kording, J. Tenenbaum Causal inference in sensorimotor integration C. Shelton, W. Huie Chained Boosting J. Vinson, D. DeCaprio, S. Luoma, J. Galagan Comparative Gene Prediction using Conditional Random Fields P. Carbonetto, N. de Freitas Conditional mean field P. Li, K. Church, T. Hastie Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data M. Mozer, M. Jones, M. Shettel Context Effects in Category Learning: An Investigation of Four Probabilistic Models M. Belkin, P. Niyogi Convergence of Laplacian Eigenmaps A. Bissacco, M. Yang, S. Soatto Detecting Humans via Their Pose J. Davis, I. Dhillon Differential Entropic Clustering of Multivariate Gaussians S. Funiak, C. Guestrin, M. Paskin, R. Sukthankar Distributed Inference in Dynamical Systems S. Avidan, M. Butman Efficient Methods for Privacy Preserving Classification H. Lee, A. Battle, R. Rajat, A. Ng Efficient sparse coding algorithms, end-stopping and nCRF surround suppression S. Lee, V. Ganapathi, D. Koller Efficient Structure Learning of Markov Networks using L1-Regularization A. Rahimi, B. Recht Estimating Observation Functions in Dynamical Systems Using Unsupervised Regression R. Kondor, T. Jebara Gaussian and Wishart Hyperkernels K. Yu, W. Chu, S. Yu, V. Tresp, Z. Xu Gaussian Process Models for Discriminative Link Prediction H. Valizadegan, R. Jin Generalized Maximum Margin Clustering and Unsupervised Kernel Learning A. Hero Geometric entropy minimization (GEM) for anomaly detection and localization K. Weinberger, F. Sha, Q. Zhu, L. Saul Graph Regularization for Maximum Variance Unfolding with an Application to Sensor Localization S. Kim, P. Smyth Hierarchical Dirichlet Processes with Random Effects A. Geramifard, M. Bowling, M. Zinkevich, R. Sutton iLSTD: Convergence, Eligibility Traces, and Mountain Car A. Frome, Y. Singer, J. Malik Image Retrieval and Classification Using Local Distance Functions L. Cheng, V. S V N, D. Schuurmans, S. Wang, T. Caelli implicit Online Learning with Kernels M. Rabbat, M. Figueiredo, R. Nowak Inferring Network Structure from Co-Occurrences Y. Mao, G. Lebanon Isotonic Conditional Random Fields and Local Sentiment Flow R. Jenssen, T. Eltoft, M. Girolami, D. Erdogmus Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm L. Torresani, K. Lee Large Margin Component Analysis A. Gore, S. Chakrabartty Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural P D. Grimes, D. Rashid, R. Rao Learning Nonparametric Models for Probabilistic Imitation R. Ando, T. Zhang Learning on Graph with Laplacian Regularization M. Raphan, E. Simoncelli Learning to be Bayesian without Supervision D. Ramanan Learning to parse images of articulated bodies C. Burges, Q. Le, R. Ragno Learning to Rank with Nonsmooth Cost Functions P. Dollar, V. Rabaud, S. Belongie Learning to Traverse Image Manifolds D. Zhou, J. Huang, B. Schölkopf Learning with Hypergraphs: Clustering, Classification, and Embedding E. Todorov Linearly-solvable Markov decision problems K. Filali, J. Bilmes Multi-dynamic Bayesian Networks C. Murray, G. Gordon Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General Sum Stochastic Games A. Argyriou, T. Evgeniou, M. Pontil Multi-Task Feature Learning C. Gomes, A. Sabharwal, B. Selman Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints A. Myronenko, X. Song Non-rigid point set registration: Coherent Point Drift C. Cortes, M. Mohri On Transductive Regression A. Yu Optimal Change-Detection and Spiking Neurons Y. Qi, T. Jaakkola Parameter Expanded Variational Bayesian Methods M. Warmuth, D. Kuzmin Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension D. Cohn, D. Verma, K. Pfleger Recursive Attribute Factoring H. Shan, L. Zhang, G. Cottrell Recursive ICA O. Boiman, M. Irani Similarity by Composition A. Rakhlin, A. Caponnetto Stability of $K$-Means Clustering P. Schrater, R. Sundareswara Theory and Dynamics of Perceptual Bistability S. Gross, O. Russakovsky, C. Do, S. Batzoglou Training Conditional Random Fields for Maximum Parse Accuracy
Tuesday
8:30am	Dan Ariely Free Lunches: Insights from Behavioral Economics
9:30am	Charles Kemp, Patrick Shafto, Allison Berke, Josh Tenenbaum Combining causal and similarity-based reasoning
9:50am	Eli Ben-Sasson, Adam Kalai, Ehud Kalai An Approach to Bounded Rationality
10:10am	Michael Lee, Ian Fuss, Daniel Navarro A Bayesian Approach to Diffusion Models of Decision-Making and Response Time
10:10am	Mohammad Ghavamzadeh, Yaakov Engel Bayesian Policy Gradient Algorithms
10:10am	Steffen Bickel, Tobias Scheffer Dirichlet-Enhanced Spam Filtering based on Biased Samples
10:10am	Sandeep Pandey, Christopher Olston Handling Advertisements of Unknown Quality in Search Advertising
10:10am	Huan Xu, Shie Mannor The Robustness-Performance Tradeoff in Markov Decision Processes
10:20am	Coffee Break
10:50am	Nathan Ratliff, David Bradley, Drew Bagnell, Joel Chestnutt Boosting Structured Prediction for Imitation Learning
11:10am	Pieter Abbeel, Adam Coates, Andrew Ng, Morgan Quigley An Application of Reinforcement Learning to Aerobatic Helicopter Flight
11:30am	Lorenzo Torresani, Peggy Hackney, Christoph Bregler Learning Motion Style Synthesis from Perceptual Observations
11:50am	Graham Taylor, Geoffrey Hinton, Sam Roweis Modeling Human Motion Using Binary Latent Variables
11:50am	Konrad Kording, Josh Tenenbaum, Reza Shadmehr Multiple timescales and uncertainty in motor adaptation
11:50am	Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Ng Robotic Grasping of Novel Objects
12:00 - 2:00pm	Lunch (2 hours)
2:00pm	Ralf Herbrich, Tom Minka, Thore Graepel TrueSkill: A Bayesian Skill Rating System
2:20pm	Lin Wu, Pierre Baldi A Scalable Machine Learning Approach to Go
2:40pm	Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary Bradski, Andrew Ng, Kunle Olukotun Map-Reduce for Machine Learning on Multicore
3:00pm	Geoffrey Gordon No-regret algorithms for Online Convex Programs
3:20pm	Shai Shalev-Shwartz, Yoram Singer Convex Repeated Games and Fenchel Duality
3:20pm	Mark Herbster, Massi Pontil Prediction on a Graph with a Perceptron
3:20pm	Ofer Dekel, Yoram Singer Support Vector Machines on a Budget
3:30pm	Coffee Break
4:00pm	Daniel Roy, Charles Kemp, Vikash Mansinghka, Josh Tenenbaum Learning annotated hierarchies from relational data
4:20pm	Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle Greedy Layer-Wise Training of Deep Networks
4:40pm	Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alexander Smola A Kernel Method for the Two-Sample-Problem
5:00pm	Kenichi Kurihara, Max Welling, Nikos Vlassis Accelerated Variational Dirichlet Process Mixtures
5:00pm	Jiayuan Huang, Alexander Smola, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf Correcting Sample Selection Bias by Unlabeled Data
5:00pm	Martin Wainwright, Pradeep Ravikumar, John Lafferty Inferring Graphical Model Structure using $\ell_1$-Regularized Pseudo-Likelihood
5:00pm	Ted Meeds, Zoubin Ghahramani, Radford Neal, Sam Roweis Modeling Dyadic Data with Binary Latent Features
5:00pm	Alexandre Lacasse, Francois Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier
5:00pm	David Barber, Silvia Chiappa Unified Inference for Variational Bayesian Linear Gaussian State-Space Models
5:00pm	John Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller Using Combinatorial Optimization within Max-Product Belief Propagation
7:30pm - 12:00am	Demonstrations
	L. Bogoni, M. Salganicoff, R. Rao, M. Dundar, B. Krishnapuram, G. Fung Computer Aided Diagnosis of Early Stage Cancer S. Raghupathy, Q. Zhang, P. Haluptzok Intelligent Ink Processing B. Fortuna, D. Mladenic, M. Grobelnik OntoGen E. Pednault, H. Toledano, R. Natarajan, A. Ghoting, E. Yom-Tov, E. Aharoni, D. Pelleg Parallel Machine Learning Toolbox B. Sapp, S. Gould, A. Kaehler, G. Bradski, A. Ng Peripheral-Foveal Vision for Real-time Object Recognition J. Bergeron, J. Lavoie, S. Loiselle, H. Anh, V. Lapointe, J. ROUAT, R. Pichevar, J. Bélanger RN-Spikes: A bio-inspired neural processor for face recognition R. Wright, J. Landay, K. Kilanski, X. Li, J. Malkin, J. Bilmes The Vocal Joystick
7:30pm - 12:00am	Poster Session
	M. Lee, I. Fuss, D. Navarro A Bayesian Approach to Diffusion Models of Decision-Making and Response Time K. Kurihara, M. Welling, N. Vlassis Accelerated Variational Dirichlet Process Mixtures M. Johnson, T. Griffiths, S. Goldwater Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Mod S. Lemm, C. Schäfer, G. Curio Aggregating Classification Accuracy through Time - Classifying Single Trial EEG A. Gretton, K. Borgwardt, M. Rasch, B. Schölkopf, A. Smola A Kernel Method for the Two-Sample-Problem Y. Kawahara, T. Yairi, K. Machida A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems J. Blitzer, S. Ben-David, K. Crammer, F. Pereira Analysis of Representations for Domain Adaptation P. Abbeel, A. Coates, A. Ng, M. Quigley An Application of Reinforcement Learning to Aerobatic Helicopter Flight E. Ben-Sasson, A. Kalai, E. Kalai An Approach to Bounded Rationality S. Selvaraj Keerthi, V. Sindhwani, O. Chapelle An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models L. Wu, P. Baldi A Scalable Machine Learning Approach to Go C. Bartolozzi, G. Indiveri A selective attention multi--chip system with dynamic synapses and spiking neurons O. Williams A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular St M. Ghavamzadeh, Y. Engel Bayesian Policy Gradient Algorithms N. Ratliff, D. Bradley, D. Bagnell, J. Chestnutt Boosting Structured Prediction for Imitation Learning C. Kemp, P. Shafto, A. Berke, J. Tenenbaum Combining causal and similarity-based reasoning K. Rieck, P. Laskov, S. Sonnenburg Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees S. Shalev-Shwartz, Y. Singer Convex Repeated Games and Fenchel Duality J. Huang, A. Smola, A. Gretton, K. Borgwardt, B. Schölkopf Correcting Sample Selection Bias by Unlabeled Data M. Braun, J. Buhmann, K. Mueller Denoising and Dimension Reduction in Feature Space S. Bickel, T. Scheffer Dirichlet-Enhanced Spam Filtering based on Biased Samples R. Zass, A. Shashua Doubly Stochastic Normalization for Spectral Clustering N. Schraudolph, S. Günter, V. S V N Fast Iterative Kernel PCA B. Nadler, M. Galun Fundamental Limitations of Spectral Clustering Methods W. Li, K. Lee, K. Leung Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle Greedy Layer-Wise Training of Deep Networks S. Pandey, C. Olston Handling Advertisements of Unknown Quality in Search Advertising J. Laub, J. Macke, K. Mueller, F. Wichmann Inducing Metric Violations in Human Similarity Judgements M. Wainwright, P. Ravikumar, J. Lafferty Inferring Graphical Model Structure using $\ell_1$-Regularized Pseudo-Likelihood Y. Seldin, N. Slonim, N. Tishby Information Bottleneck for Non Co-Occurrence Data S. Klampfl, R. Legenstein, W. Maass Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons D. Roy, C. Kemp, V. Mansinghka, J. Tenenbaum Learning annotated hierarchies from relational data K. Crammer, M. Kearns, J. Wortman Vaughan Learning from Multiple Sources L. Torresani, P. Hackney, C. Bregler Learning Motion Style Synthesis from Perceptual Observations A. Ihler, P. Smyth Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models C. Chu, S. Kim, Y. Lin, Y. Yu, G. Bradski, A. Ng, K. Olukotun Map-Reduce for Machine Learning on Multicore A. Storkey, M. Sugiyama Mixture Regression for Covariate Shift J. Wang, Z. Zhang MLLE: Modified Locally Linear Embedding Using Multiple Weights T. Meeds, Z. Ghahramani, R. Neal, S. Roweis Modeling Dyadic Data with Binary Latent Features G. Taylor, G. Hinton, S. Roweis Modeling Human Motion Using Binary Latent Variables G. Fung, M. Dundar, B. Krishnapuram, R. Rao Multiple Instance Learning for Computer Aided Diagnosis K. Kording, J. Tenenbaum, R. Shadmehr Multiple timescales and uncertainty in motor adaptation G. Gordon No-regret algorithms for Online Convex Programs R. Vidal Online Clustering of Moving Subspaces H. Narayanan, M. Belkin, P. Niyogi On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts R. El-Yaniv, M. Nisenson Optimal Single-Class Classification Strategies A. Lacasse, F. Laviolette, M. Marchand, P. Germain, N. Usunier PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier G. McNeill, S. Vijayakumar Part-based Probabilistic Point Matching using Equivalence Constraints R. Kobayashi, S. Shinomoto Predicting spike times from subthreshold dynamics of a neuron M. Herbster, M. Pontil Prediction on a Graph with a Perceptron F. Moosmann, B. Triggs, F. JURIE Randomized Clustering Forests for Building Fast and Discriminative Visual Vocabularies A. Saxena, J. Driemeyer, J. Kearns, A. Ng Robotic Grasping of Novel Objects P. Bartlett, A. Tewari Sample Complexity of Policy Search with Known Dynamics K. Zhang, J. Kwok Simplifying Mixture Models through Function Approximation J. Arenas-García, K. Petersen, L. Hansen Sparse Kernel Orthonormalized PLS for feature extraction in large data sets G. Cawley, N. Talbot, M. Girolami Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation G. Haro, G. Randall, G. Sapiro Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds O. Dekel, Y. Singer Support Vector Machines on a Budget T. Voegtlin Temporal Coding using the Response Properties of Spiking Neurons T. Ott, R. Stoop The Neurodynamics of Belief Propagation on Binary Markov Random Fields H. Xu, S. Mannor The Robustness-Performance Tradeoff in Markov Decision Processes A. Ambroladze, E. Parrado-Hernandez, J. Shawe-Taylor Tighter PAC-Bayes Bounds R. Herbrich, T. Minka, T. Graepel TrueSkill: A Bayesian Skill Rating System D. Barber, S. Chiappa Unified Inference for Variational Bayesian Linear Gaussian State-Space Models J. Duchi, D. Tarlow, G. Elidan, D. Koller Using Combinatorial Optimization within Max-Product Belief Propagation
Wednesday
8:30am	George Ojemann Examining the Human Brain Mechanisms for Language, Memory, and Learning During Awake Neurosurgery
9:30am	Mate Lengyel, Peter Dayan Uncertainty, phase and oscillatory hippocampal recall
9:50am	Jeremy Lewi, Robert Butera, Liam Paninski Real-time adaptive information-theoretic optimization of neurophysiological experiments
10:10am	Alexis Battle, Gal Chechik, Daphne Koller Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Task
10:30am	Coffee Break
11:00am	Matthias Hein, Markus Maier Manifold Denoising
11:20am	Ivor Tsang, James Kwok Large-Scale Sparsified Manifold Regularization
11:40am	Marc'Aurelio Ranzato, Christopher Poultney, Sumit Chopra, Yann LeCun Efficient Learning of Sparse Representations with an Energy-Based Model
11:40am	Yi Li, Phil Long Learnability and the doubling dimension
11:40am	Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller Max-margin classification of incomplete data
11:40am	Zhi-Hua Zhou, Min-Ling Zhang Multi-Instance Multi-Label Learning with Application to Scene Classification
11:40am	Ling Li, Hsuan-Tien Lin Ordinal Regression by Extended Binary Classification
11:40am	Joseph Turian, Benjamin Wellington, Dan Melamed Scalable Discriminative Learning for Natural Language Parsing and Translation
12:00 - 2:00pm	Lunch (2 hours)
2:00pm	David Baker Global Optimization Challenges in High Resolution Protein Structure Prediction
3:00pm	KyungAh Sohn, Eric Xing A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space
3:20pm	David Wipf, Rey Ramirez, Jason Palmer, Scott Makeig, Bhaskar Rao Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization
3:20pm	Hideaki Shimazaki, Shigeru Shinomoto A recipe for optimizing a time-histogram
3:20pm	Jennifer Listgarten, Radford Neal, Sam Roweis, Rachel Puckrin, Sean Cutler Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure
3:20pm	Elisabetta Chicca, Giacomo Indiveri, Rodney Douglas Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons
3:20pm	Luis Perez-Breva, Luis Ortiz, Chen-Hsiang Yeang, Tommi Jaakkola Game Theoretic Algorithms for Protein-DNA binding
3:20pm	Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Mueller Logistic Regression for Single Trial EEG Classification
3:20pm	Tobias Sing, Niko Beerenwinkel Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype
3:30pm	Coffee Break
4:00pm	Anitha Kannan, John Winn, Carsten Rother Clustering appearance and shape by learning jigsaws
4:20pm	Jonathan Harel, Christof Koch, Pietro Perona Graph-Based Visual Saliency
4:40pm	Ce Liu, William Freeman, Edward Adelson Analysis of Contour Motions
5:00pm	Fei Sha, Lawrence Saul Large Margin Gaussian Mixture Models for Automatic Speech Recognition
5:20pm	Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-Or, Eytan Ruppin A Humanlike Predictor of Facial Attractiveness
5:20pm	Kristen Grauman, Trevor Darrell Approximate Correspondences in High Dimensions
5:20pm	Eizaburo Doi, Michael Lewicki A Theory of Retinal Population Coding
5:20pm	Lyndsey Pickup, David Capel, Stephen Roberts, Andrew Zisserman Bayesian Image Super-resolution, Continued
5:20pm	John Hershey, Trausti Kristjansson, Steven Rennie, Peder Olsen Single Channel Speech Separation Using Layered Hidden Markov Models
5:20pm	Roger Levy, T. Florian Jaeger Speakers optimize information density through syntactic reduction
5:20pm	Aharon Bar Hillel, Daphna Weinshall Subordinate class recognition using relational object models
7:30pm - 12:00am	Poster Session
	F. Bach Active learning for misspecified generalized linear models M. Grosse-Wentrup, K. Gramann, M. Buss Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces K. Sohn, E. Xing A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space A. Kagian, G. Dror, T. Leyvand, D. Cohen-Or, E. Ruppin A Humanlike Predictor of Facial Attractiveness M. Wu, B. Schölkopf A Local Learning Approach for Clustering C. Liu, W. Freeman, E. Adelson Analysis of Contour Motions D. Wipf, R. Ramirez, J. Palmer, S. Makeig, B. Rao Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization M. Mandel, D. Ellis, T. Jebara An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments I. Steinwart, D. Hush, C. Scovel An Oracle Inequality for Clipped Regularized Risk Minimizers D. Barber, B. Mesot A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical P. Germain, A. Lacasse, F. Laviolette, M. Marchand A PAC-Bayes Risk Bound for General Loss Functions K. Grauman, T. Darrell Approximate Correspondences in High Dimensions A. Globerson, T. Jaakkola Approximate inference using planar graph decomposition H. Shimazaki, S. Shinomoto A recipe for optimizing a time-histogram E. Doi, M. Lewicki A Theory of Retinal Population Coding J. Listgarten, R. Neal, S. Roweis, R. Puckrin, S. Cutler Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure H. Chipman, E. George, R. McCulloch Bayesian Ensemble Learning L. Pickup, D. Capel, S. Roberts, A. Zisserman Bayesian Image Super-resolution, Continued L. Omlor, M. Giese Blind source separation for over-determined delayed mixtures A. Kannan, J. Winn, C. Rother Clustering appearance and shape by learning jigsaws M. Figueiredo, D. Cheng, V. Murino Clustering Under Prior Knowledge with Application to Image Segmentation E. Chicca, G. Indiveri, R. Douglas Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons M. Seeger Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods M. Girolami, M. Zhong Data Integration for Classification Problems Employing Gaussian Process Priors L. Huang, X. Nguyen, M. Garofalakis, M. Jordan, A. Joseph, N. Taft Distributed PCA and Network Anomaly Detection L. Lu, G. Hager Dynamic Foreground/Background Extraction from Images and Videos using Random Patches G. Luksys, J. Knuesel, D. Sheynikhovich, C. Sandi, W. Gerstner Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning M. Ranzato, C. Poultney, S. Chopra, Y. LeCun Efficient Learning of Sparse Representations with an Energy-Based Model J. Lindgren, A. Hyvärinen Emergence of conjunctive visual features by quadratic independent component analysis V. S V N, K. Borgwardt, N. Schraudolph Fast Computation of Graph Kernels L. Perez-Breva, L. Ortiz, C. Yeang, T. Jaakkola Game Theoretic Algorithms for Protein-DNA binding J. Harel, C. Koch, P. Perona Graph-Based Visual Saliency X. Zhang, W. Lee Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms C. Walder, B. Schölkopf, O. Chapelle Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions M. Cuturi, K. Fukumizu Kernels on Structured Objects Through Nested Histograms I. Tsang, J. Kwok Large-Scale Sparsified Manifold Regularization F. Sha, L. Saul Large Margin Gaussian Mixture Models for Automatic Speech Recognition G. Raetsch, S. Sonnenburg Large Scale Hidden Semi-Markov SVMs Y. Li, P. Long Learnability and the doubling dimension F. Steinke, B. Schölkopf, V. Blanz Learning Dense 3D Correspondence A. Storkey, E. Simonotto, H. Whalley, S. Lawrie, L. Murray, D. McGonigle Learning Structural Equation Models for fMRI C. Lee, S. Wang, F. Jiao, D. Schuurmans, R. Greiner Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields P. Auer, R. Ortner Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning R. Tomioka, K. Aihara, K. Mueller Logistic Regression for Single Trial EEG Classification M. Hein, M. Maier Manifold Denoising G. Chechik, G. Heitz, G. Elidan, P. Abbeel, D. Koller Max-margin classification of incomplete data C. Chemudugunta, P. Smyth, M. Steyvers Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model N. Lawrence, G. Sanguinetti, M. Rattray Modelling transcriptional regulation using Gaussian Processes Z. Zhou, M. Zhang Multi-Instance Multi-Label Learning with Application to Scene Classification T. Sing, N. Beerenwinkel Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype S. Richter, D. Aberdeen, J. Yu Natural Actor-Critic for Road Traffic Optimisation J. Samonds, B. Potetz, T. Lee Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation G. Shakhnarovich, S. Kim, M. Black Nonlinear physically-based models for decoding motor-cortical population activity R. Zass, A. Shashua Nonnegative Sparse PCA Y. Amit, S. Shalev-Shwartz, Y. Singer Online Classification for Complex Problems Using Simultaneous Projections L. Li, H. Lin Ordinal Regression by Extended Binary Classification F. Wood, T. Griffiths Particle Filtering for Nonparametric Bayesian Matrix Factorization Y. Feng, G. Hamerly PG-means: learning the number of clusters in data J. Lewi, R. Butera, L. Paninski Real-time adaptive information-theoretic optimization of neurophysiological experiments W. Chu, V. Sindhwani, Z. Ghahramani, S. Selvaraj Keerthi Relational Learning with Gaussian Processes J. Turian, B. Wellington, D. Melamed Scalable Discriminative Learning for Natural Language Parsing and Translation B. Rubinstein, P. Bartlett, J. Rubinstein Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds J. Hershey, T. Kristjansson, S. Rennie, P. Olsen Single Channel Speech Separation Using Layered Hidden Markov Models K. Huang, S. Aviyente Sparse Representation for Signal Classification R. Levy, T. Jaeger Speakers optimize information density through syntactic reduction S. Lyu, E. Simoncelli Statistical Modeling of Images with Fields of Gaussian Scale Mixtures S. Parise, M. Welling Structure Learning in Markov Random Fields A. Bar Hillel, D. Weinshall Subordinate class recognition using relational object models A. Battle, G. Chechik, D. Koller Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Task D. Nikolic, S. Haeusler, W. Singer, W. Maass Temporal dynamics of information content carried by neurons in the primary visual cortex F. Theis Towards a general independent subspace analysis M. Krauledat, M. Schröder, B. Blankertz, K. Mueller Towards Zero-Training for Brain-Computer Interface Experiments M. Lengyel, P. Dayan Uncertainty, phase and oscillatory hippocampal recall L. Zhu, Y. Chen, A. Yuille Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
Thursday
8:30am	Daniel Margoliash Neural Mechanisms of Auditory Pattern Processing and Pattern Learning in Songbirds
8:30 - 11:00am	Morning session - speaker information will be available soon
9:30am	Long Zhu, Yuanhao Chen, Alan Yuille Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
9:50am	Coffee Break
10:20am	Hugh Chipman, Edward George, Robert McCulloch Bayesian Ensemble Learning
10:40am	Amir Globerson, Tommi Jaakkola Approximate inference using planar graph decomposition
11:00am	James Clark Emerging Capacity to Synthesize Data and Process: Application to the Biodiversity Paradox
11:00am	Conference End

The schedule was last modified on 2009-12-9 09:48 PST