Schedule

Tutorials (December 7, 2009)

Sunday, December 6
4:00 - 8:00pm	Registration Desk
Monday, December 7
7:30 - 9:00am	Breakfast - Regency A, Conference Level
8:00am - 6:00pm	Registration Desk, Internet Cafe
9:30 - 11:30am	Gunnar Martinsson Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization
9:30 - 11:30am	Antonio Torralba Understanding Visual Scenes
11:30am - 1:00pm	Lunch Break
1:00 - 3:00pm	Michael L Littman Model-Based Reinforcement Learning
1:00 - 3:00pm	Francis Bach Sparse Methods for Machine Learning: Theory and Algorithms
3:00 - 3:30pm	Break
3:30 - 5:30pm	Ronan Collobert, Jason E Weston Deep Learning in Natural Language Processing
3:30 - 5:30pm	Arnaud Doucet, Nando de Freitas Sequential Monte-Carlo Methods

Conference Sessions (December 7-10, 2009)

Monday, December 7
8:00am - 6:00pm	Registration Desk, Internet Cafe
6:15 - 6:30pm	Opening Remarks and Awards
6:30 - 6:50pm	Spotlights
	H. Valizadegan, R. Jin, R. Zhang, J. Mao Learning to Rank by Optimizing NDCG Measure R. Arora On Learning Rotations M. Kolar, L. Song, E. Xing Sparsistent Learning of Varying-coefficient Models with Structural Changes S. Klampfl, W. Maass Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks Z. Yang, I. King, Z. Xu, E. Oja Heavy-Tailed Symmetric Stochastic Neighbor Embedding V. Rao, Y. Teh Spatial Normalized Gamma Processes H. Wallach, D. Mimno, A. McCallum Rethinking LDA: Why Priors Matter K. Miller, T. Griffiths, M. Jordan Nonparametric Latent Feature Models for Link Prediction A. Gretton, K. Fukumizu, Z. Harchaoui, B. Sriperumbudur A Fast, Consistent Kernel Two-Sample Test A. Subramanya, J. Bilmes Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification S. Rangan, A. Fletcher, V. Goyal Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing I. Steinwart, A. Christmann Fast Learning from Non-i.i.d. Observations H. Maei, C. Szepesvari, S. Batnaghar, D. Precup, D. Silver, R. Sutton Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation
7:00 - 11:59pm	Poster Session
	A. Subramanya, J. Bilmes M1 Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification P. Smaragdis, M. Shashanka, B. Raj M2 A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds J. Honorio, L. Ortiz, D. Samaras, N. Paragios, R. Goldstein M3 Sparse and Locally Constant Gaussian Graphical Models P. Carbonetto, M. King, F. Hamze M4 A Stochastic approximation method for inference in probabilistic graphical models C. Wang, D. Blei M5 Variational Inference for the Nested Chinese Restaurant Process J. Vanhatalo, P. Jylänki, A. Vehtari M6 Gaussian process regression with Student-t likelihood R. Socher, S. Gershman, A. Perotte, P. Sederberg, D. Blei, K. Norman M7 A Bayesian Analysis of Dynamics in Free Recall B. Van Durme, A. Lall M8 Streaming Pointwise Mutual Information M. Grzegorczyk, D. Husmeier M9 Non-stationary continuous dynamic Bayesian networks V. Rao, Y. Teh M10 Spatial Normalized Gamma Processes M. Kumar, D. Koller M11 Learning a Small Mixture of Trees A. Montanari, J. Bento M12 Which graphical models are difficult to learn? S. Mohamed, D. Knowles, Z. Ghahramani, F. Doshi-Velez M13 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process I. Sutskever, R. Salakhutdinov, J. Tenenbaum M14 Modelling Relational Data using Bayesian Clustered Tensor Factorization K. Miller, T. Griffiths, M. Jordan M15 Nonparametric Latent Feature Models for Link Prediction S. Rangan, A. Fletcher, V. Goyal M16 Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing M. Wilder, M. Jones, M. Mozer M17 Sequential effects reflect parallel learning of multiple environmental regularities Z. Yang, Q. Zhao, E. Keefer, W. Liu M18 Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording R. Brasselet, R. Johansson, A. Arleo M19 Optimal context separation of spiking haptic signals by second-order somatosensory neurons J. Macke, S. Gerwinn, L. White, M. Kaschube, M. Bethge M20 Bayesian estimation of orientation preference maps S. Klampfl, W. Maass M21 Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks B. Conroy, B. Singer, J. Haxby, P. Ramadge M22 fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity A. Onken, S. Grünewälder, K. Obermayer M23 Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies Y. Fujiwara, Y. Miyawaki, Y. Kamitani M24 Estimating image bases for visual image reconstruction from human brain activity T. Hu, A. Leonardo, D. Chklovskii M25 Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) M. Blaschko, J. Shelton, A. Bartels M26 Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity C. Boutsidis, M. Mahoney, P. Drineas M27 Unsupervised Feature Selection for the $k$-means Clustering Problem J. Wright, A. Balasubramanian, S. Rao, Y. Peng, Y. Ma M28 Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization A. Kapoor, E. Horvitz M29 Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition K. Bush, J. Pineau M30 Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability T. Iwata, T. Yamada, N. Ueda M31 Modeling Social Annotation Data with Content Relevance using a Topic Model P. Ram, D. Lee, H. Ouyang, A. Gray M32 Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions N. Quadrianto, J. Petterson, A. Smola M33 Distribution Matching for Transduction Z. Yang, I. King, Z. Xu, E. Oja M34 Heavy-Tailed Symmetric Stochastic Neighbor Embedding Y. Wang, G. Haffari, S. Wang, G. Mori M35 A Rate Distortion Approach for Semi-Supervised Conditional Random Fields Z. Zhang, g. dai M36 Optimal Scoring for Unsupervised Learning G. Chechik, U. Shalit, V. Sharma, S. Bengio M37 An Online Algorithm for Large Scale Image Similarity Learning H. Wallach, D. Mimno, A. McCallum M38 Rethinking LDA: Why Priors Matter K. Sinha, M. Belkin M39 Semi-supervised Learning using Sparse Eigenfunction Bases N. Ailon, R. Jaiswal, C. Monteleoni M40 Streaming k-means approximation B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, C. Cortes, M. Mohri M41 Polynomial Semantic Indexing R. Meka, P. Jain, I. Dhillon M42 Matrix Completion from Power-Law Distributed Samples T. Ouyang, R. Davis M43 Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, j. movellan M44 Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise C. Kemp, A. Jern, F. Xu M45 Individuation, Identification and Object Discovery M. Steyvers, M. Lee, B. Miller, P. Hemmer M46 The Wisdom of Crowds in the Recollection of Order Information W. Vanpaemel M47 Measuring model complexity with the prior predictive A. Vedaldi, A. Zisserman M48 Structured output regression for detection with partial truncation L. Xiao M49 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization K. Chai M50 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes P. Zhao, S. Hoi, R. Jin M51 DUOL: A Double Updating Approach for Online Learning M. Lanctot, K. Waugh, M. Zinkevich, M. Bowling M52 Monte Carlo Sampling for Regret Minimization in Extensive Games E. Hazan, S. Kale M53 Beyond Convexity: Online Submodular Minimization P. Liang, F. Bach, G. Bouchard, M. Jordan M54 Asymptotically Optimal Regularization in Smooth Parametric Models O. Maillard, R. Munos M55 Compressed Least-Squares Regression M. Hein M56 Robust Nonparametric Regression with Metric-Space Valued Output J. Bouvrie, L. Rosasco, T. Poggio M57 On Invariance in Hierarchical Models I. Steinwart, A. Christmann M58 Fast Learning from Non-i.i.d. Observations C. Hsu, Y. Chang, H. Huang, Y. Lee M59 Periodic Step Size Adaptation for Single Pass On-line Learning L. Zhu, Y. Chen, B. Freeman, A. Torralba M60 Nonparametric Bayesian Texture Learning and Synthesis D. Zoran, Y. Weiss M61 The "tree-dependent components" of natural scenes are edge filters S. Ghebreab, H. Steven, V. Lamme, A. Smeulders M62 A Biologically Plausible Model for Rapid Natural Scene Identification J. Schlecht, K. Barnard M63 Learning models of object structure S. Yang, H. Zha, B. Hu M64 Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora D. Margaritis M65 Toward Provably Correct Feature Selection in Arbitrary Domains S. Clémençon, N. Vayatis, M. Depecker M66 AUC optimization and the two-sample problem H. Valizadegan, R. Jin, R. Zhang, J. Mao M67 Learning to Rank by Optimizing NDCG Measure R. Arora M68 On Learning Rotations M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell M69 Zero-shot Learning with Semantic Output Codes W. Chen, T. Liu, Y. Lan, Z. Ma, H. Li M70 Ranking Measures and Loss Functions in Learning to Rank M. Brückner, T. Scheffer M71 Nash Equilibria of Static Prediction Games M. Kolar, L. Song, E. Xing M72 Sparsistent Learning of Varying-coefficient Models with Structural Changes M. Karasuyama, I. Takeuchi M73 Multiple Incremental Decremental Learning of Support Vector Machines S. Jagarlapudi, d. govindaraj, R. S, C. Bhattacharyya, A. Ben-Tal, K. Ramakrishnan M74 On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation J. Gao, F. Liang, W. Fan, Y. Sun, J. Han M75 Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models C. Shen, J. Kim, L. Wang, A. van den Hengel M76 Positive Semidefinite Metric Learning with Boosting A. Perina, M. Cristani, U. Castellani, V. Murino, N. Jojic M77 Free energy score space J. Peng, L. Bo, J. Xu M78 Conditional Neural Fields O. Dekel M79 Distribution-Calibrated Hierarchical Classification V. Cevher M80 Learning with Compressible Priors A. Gretton, K. Fukumizu, Z. Harchaoui, B. Sriperumbudur M81 A Fast, Consistent Kernel Two-Sample Test G. Shani, C. Meek M82 Improving Existing Fault Recovery Policies H. Sprekeler, G. Hennequin, W. Gerstner M83 Code-specific policy gradient rules for spiking neurons T. Morimura, E. Uchibe, J. Yoshimoto, K. Doya M84 A Generalized Natural Actor-Critic Algorithm H. Maei, C. Szepesvari, S. Batnaghar, D. Precup, D. Silver, R. Sutton M85 Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation L. Mac Dermed, C. Isbell M86 Solving Stochastic Games M. Cuturi, J. Vert, A. d'Aspremont M87 White Functionals for Anomaly Detection in Dynamical Systems
Tuesday, December 8
7:30 - 9:00am	Breakfast
8:00am - 6:00pm	Registration Desk, Internet Cafe
8:30 - 10:10am	Oral Session 1: Information Theory and EstimationSession Chair:Rob Nowak
	Sergio Verdu Relative Entropy D. Hsu, S. Kakade, J. Langford, T. Zhang Multi-Label Prediction via Compressed Sensing S. Negahban, P. Ravikumar, M. Wainwright, B. Yu A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
10:10 - 10:40am	Break
10:40am - 12:00pm	Oral Session 2: Images and CodesSession Chair:Bill Triggs
	M. Fritz, M. Black, G. Bradski, T. Darrell An Additive Latent Feature Model for Transparent Object Recognition R. Fergus, Y. Weiss, A. Torralba Semi-Supervised Learning in Gigantic Image Collections M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations M. Raginsky, S. Lazebnik Locality-Sensitive Binary Codes from Shift-Invariant Kernels
12:00 - 2:00pm	Lunch Break
12:30 - 1:45pm	Yoshua Bengio Debate on Future Publication Models for the NIPS Community
2:00 - 3:20pm	Oral Session 3: Deep Learning and Network ModelsSession Chair:Aaron C Courville
	Geoffrey E Hinton Deep Learning with Multiplicative Interactions G. Cecchi, I. Rish, B. Thyreau, B. Thirion, M. Plaze, J. Martinot, M. Paillere-Martinot, J. Poline Discriminative Network Models of Schizophrenia
3:20 - 3:40pm	Spotlights
	P. Sollich, M. Urry, C. Coti Kernels and learning curves for Gaussian process regression on random graphs M. Petrik, S. Zilberstein Robust Value Function Approximation Using Bilinear Programming Y. Ying, C. Campbell, M. Girolami Analysis of SVM with Indefinite Kernels Z. Xiang, Y. Xi, U. Hasson, P. Ramadge Boosting with Spatial Regularization C. Kemp, A. Jern Abstraction and Relational learning W. Li, D. Yeung, Z. Zhang Probabilistic Relational PCA C. Wang, D. Blei Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process S. Gerwinn, P. Berens, M. Bethge A joint maximum-entropy model for binary neural population patterns and continuous signals L. Cayton Efficient Bregman Range Search Y. Watanabe, K. Fukumizu Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation M. Streeter, D. Golovin, A. Krause Online Learning of Assignments P. Ram, D. Lee, W. March, A. Gray Linear-time Algorithms for Pairwise Statistical Problems
3:40 - 4:10pm	Break
4:10 - 5:10pm	Oral Session 4: Cognitive Science and EEG AnalysisSession Chair:Charles Kemp
	A. Hsu, T. Griffiths Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning E. Vul, M. Frank, G. Alvarez, J. Tenenbaum Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model W. Zheng, Z. Lin Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification
5:10 - 5:30pm	Spotlights
	Y. Teh, D. Gorur Indian Buffet Processes with Power-law Behavior Y. Kawahara, K. Nagano, K. Tsuda, J. Bilmes Submodularity Cuts and Applications R. Coen-Cagli, P. Dayan, O. Schwartz Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing B. Nessler, M. Pfeiffer, W. Maass STDP enables spiking neurons to detect hidden causes of their inputs V. Nair, G. Hinton 3D Object Recognition with Deep Belief Nets T. Perkins Maximum likelihood trajectories for continuous-time Markov chains L. Song, M. Kolar, E. Xing Time-Varying Dynamic Bayesian Networks P. Orbanz Construction of Nonparametric Bayesian Models from Parametric Bayes Equations M. Wick, K. Rohanimanesh, S. Singh, A. McCallum Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference J. Huang, C. Guestrin Riffled Independence for Ranked Data V. Desai, V. Farias, C. Moallemi A Smoothed Approximate Linear Program A. Bouchard-Côté, S. Petrov, D. Klein Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs S. Fazli, C. Grozea, M. Danóczy, B. Blankertz, F. Popescu, K. Müller Subject independent EEG-based BCI decoding
5:30 - 7:30pm	Dinner Break
7:30 - 11:59pm	Poster Session
	P. Sollich, M. Urry, C. Coti T1 Kernels and learning curves for Gaussian process regression on random graphs M. Raginsky, S. Lazebnik T2 Locality-sensitive binary codes from shift-invariant kernels W. Li, D. Yeung, Z. Zhang T3 Probabilistic Relational PCA C. Wang, D. Blei T4 Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process L. Cayton T5 Efficient Bregman Range Search L. Wu, R. Jin, S. Hoi, J. Zhu, N. Yu T6 Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering M. Schmidt T7 Linearly constrained Bayesian matrix factorization for blind source separation R. Keshavan, A. Montanari, S. Oh T8 Matrix Completion from Noisy Entries K. Yu, T. Zhang, Y. Gong T9 Nonlinear Learning using Local Coordinate Coding K. Kim, F. Steinke, M. Hein T10 Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction S. Bengio, F. Pereira, Y. Singer, D. Strelow T11 Group Sparse Coding A. Guillory, J. Bilmes T12 Label Selection on Graphs K. Jung, P. Kohli, D. Shah T13 Local Rules for Global MAP: When Do They Work ? M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin T14 Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations J. Petterson, T. Caetano, J. McAuley, J. Yu T15 Exponential Family Graph Matching and Ranking P. Coquelin, R. Deguest, R. Munos T16 Sensitivity analysis in HMMs with application to likelihood maximization J. Goldberger, A. Leshem T17 A Gaussian Tree Approximation for Integer Least-Squares N. Ye, L. Sun, H. Chieu, D. Wu T18 Conditional Random Fields with High-Order Features for Sequence Labeling Y. Watanabe, K. Fukumizu T19 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation Y. Teh, D. Gorur T20 Indian Buffet Processes with Power-law Behavior M. Lázaro-Gredilla, A. Figueiras-Vidal T21 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features R. Henao, O. Winther T22 Bayesian Sparse Factor Models and DAGs Inference and Comparison R. Salakhutdinov T23 Learning in Markov Random Fields using Tempered Transitions T. Perkins T24 Maximum likelihood trajectories for continuous-time Markov chains J. Huang, C. Guestrin T25 Riffled Independence for Ranked Data R. Tillman, A. Gretton, P. Spirtes T26 Nonlinear directed acyclic structure learning with weakly additive noise models C. Kemp, A. Jern T27 Abstraction and Relational learning X. Zhu, T. Rogers, B. Gibson T28 Human Rademacher Complexity F. Yan, N. XU, Y. Qi T29 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units A. Hsu, T. Griffiths T30 Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning D. Cavagnaro, M. Pitt, J. Myung T31 Adaptive Design Optimization in Experiments with People E. Vul, M. Frank, G. Alvarez, J. Tenenbaum T32 Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model Y. Chen, M. Kapralov, D. Pavlov, J. Canny T33 Factor Modeling for Advertisement Targeting J. Kim, S. Choi T34 Clustering sequence sets for motif discovery L. Song, M. Kolar, E. Xing T35 Time-Varying Dynamic Bayesian Networks A. Bouchard-Côté, S. Petrov, D. Klein T36 Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs D. Hsu, S. Kakade, J. Langford, T. Zhang T38 Multi-Label Prediction via Compressed Sensing S. Arlot, F. Bach T39 Data-driven calibration of linear estimators with minimal penalties R. Jin, S. Wang, Y. Zhou T40 Regularized Distance Metric Learning:Theory and Algorithm M. Streeter, D. Golovin, A. Krause T41 Online Learning of Assignments Y. Yu, Y. Li, D. Schuurmans, C. Szepesvari T42 A General Projection Property for Distribution Families Y. Kawahara, K. Nagano, K. Tsuda, J. Bilmes T43 Submodularity Cuts and Applications P. Ram, D. Lee, W. March, A. Gray T44 Linear-time Algorithms for Pairwise Statistical Problems B. Sriperumbudur, G. Lanckriet T45 On the Convergence of the Concave-Convex Procedure M. Zinkevich, A. Smola, J. Langford T46 Slow Learners are Fast C. Hu, J. Kwok, W. Pan T47 Accelerated Gradient Methods for Stochastic Optimization and Online Learning R. Nowak T48 Noisy Generalized Binary Search S. Zhou T49 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation P. Orbanz T50 Construction of Nonparametric Bayesian Models from Parametric Bayes Equations U. Syed, A. Slivkins, N. Mishra T51 Adapting to the Shifting Intent of Search Queries S. Negahban, P. Ravikumar, M. Wainwright, B. Yu T52 A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers T. Malisiewicz, A. Efros T53 Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships A. Dalalyan, R. Keriven T54 $L_1$-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry M. Fritz, M. Black, G. Bradski, T. Darrell T55 An Additive Latent Feature Model for Transparent Object Recognition R. Fergus, Y. Weiss, A. Torralba T56 Semi-Supervised Learning in Gigantic Image Collections W. Campbell, Z. Karam, D. Sturim T57 Speaker Comparison with Inner Product Discriminant Functions L. Sun, J. Liu, J. Chen, J. Ye T58 Efficient Recovery of Jointly Sparse Vectors y. meng, B. Shi T59 Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out M. Leordeanu, M. Hebert, R. Sukthankar T60 An Integer Projected Fixed Point Method for Graph Matching and MAP Inference K. Saenko, T. Darrell T61 Filtering Abstract Senses From Image Search Results W. Zheng, Z. Lin T62 Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification P. Berkes, B. White, J. Fiser T63 No evidence for active sparsification in the visual cortex S. Gerwinn, P. Berens, M. Bethge T64 A joint maximum-entropy model for binary neural population patterns and continuous signals H. Lee, P. Pham, Y. Largman, A. Ng T65 Unsupervised feature learning for audio classification using convolutional deep belief networks B. Yao, D. Walther, D. Beck, F. Li T66 Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions R. Coen-Cagli, P. Dayan, O. Schwartz T67 Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing G. Cecchi, I. Rish, B. Thyreau, B. Thirion, M. Plaze, M. Paillere-Martinot, J. Martinot, J. Poline T68 Discriminative Network Models of Schizophrenia B. Nessler, M. Pfeiffer, W. Maass T69 STDP enables spiking neurons to detect hidden causes of their inputs R. Wilson, L. Finkel T70 A Neural Implementation of the Kalman Filter M. Seeger T71 Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing S. Fazli, C. Grozea, M. Danóczy, B. Blankertz, F. Popescu, K. Müller T72 Subject independent EEG-based BCI decoding Y. Ying, C. Campbell, M. Girolami T73 Analysis of SVM with Indefinite Kernels Z. Xiang, Y. Xi, U. Hasson, P. Ramadge T74 Boosting with Spatial Regularization Y. Kao, B. Van Roy, X. Yan T75 Directed Regression I. Goodfellow, Q. Le, A. Saxe, A. Ng T76 Measuring Invariances in Deep Networks H. Liu, X. Chen T77 Nonparametric Greedy Algorithms for the Sparse Learning Problem C. Cortes, M. Mohri, A. Rostamizadeh T78 Learning Non-Linear Combinations of Kernels V. Nair, G. Hinton T79 3D Object Recognition with Deep Belief Nets A. Lozano, G. Swirszcz, N. Abe T80 Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K. Müller, A. Zien T81 Efficient and Accurate Lp-Norm Multiple Kernel Learning M. Wick, K. Rohanimanesh, S. Singh, A. McCallum T82 Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference S. Kpotufe T83 Fast, smooth and adaptive regression in metric spaces M. Petrik, S. Zilberstein T84 Robust Value Function Approximation Using Bilinear Programming F. Doshi-Velez T85 The Infinite Partially Observable Markov Decision Process V. Desai, V. Farias, C. Moallemi T86 A Smoothed Approximate Linear Program C. Cai, X. Liao, L. Carin T87 Learning to Explore and Exploit in POMDPs E. Todorov T88 Compositionality of optimal control laws R. Anati, K. Daniilidis T89 Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection
7:30 - 11:59pm	Demonstrations
	J. Frank Activity Recognition and Human Gait Recognition J. Gamez de Leon Automatically Adaptable Spike Sorting Software H. Neven Car Detector trained with the Quantum Adiabatic Algorithm I. Guyon Causality Workbench M. Depecker Demonstration of the TreeRank Software V. Mansinghka The IID: A Natively Probabilistic Reconfigurable Computer J. Niemasik Vision Toolkit for Image Recognition
Wednesday, December 9
7:30 - 9:00am	Breakfast
8:00am - 6:00pm	Registration Desk, Internet Cafe
8:30 - 10:10am	Oral Session 5: NeuroscienceSession Chair:Tai Sing Lee
	Mitra Hartmann The Rat Vibrissal Array as a Model Sensorimotor System R. Legenstein, S. Chase, A. Schwartz, W. Maass Functional Network Reorganization In Motor Cortex Can Be Explained by Reward-Modulated Hebbian Learning J. Pfister, P. Dayan, M. Lengyel Know Thy Neighbour: A Normative Theory of Synaptic Depression
10:10 - 10:40am	Break
10:40am - 12:00pm	Oral Session 6: Theory, Optimization and Games Session Chair:Ben Taskar
	J. Duchi, Y. Singer Efficient Learning using Forward-Backward Splitting E. Hazan, S. Kale On Stochastic and Worst-case Models for Investing J. Veness, D. Silver, W. Uther, A. Blair Bootstrapping from Game Tree Search B. Sriperumbudur, K. Fukumizu, A. Gretton, G. Lanckriet, B. Schölkopf Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
12:00 - 2:00pm	Lunch Break
2:00 - 3:20pm	Oral session 7: Vision and InferenceSession Chair:Antonio Torralba
	Yair Weiss Learning and Inference in Low-Level Vision M. Fromer, A. Globerson An LP View of the M-Best MAP Problem
3:20 - 3:40pm	Spotlights
	C. Kemp Quantification and the language of thought D. Krishnan, R. Fergus Fast Image Deconvolution using Hyper-Laplacian Priors G. Mann, R. McDonald, M. Mohri, N. Silberman, D. Walker Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models V. Farias, S. Jagabathula, D. Shah A Data-Driven Approach to Modeling Choice B. Nadler, N. Srebro, X. Zhou Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data S. Gould, T. Gao, D. Koller Region-based Segmentation and Object Detection M. Zhao, V. Saligrama Anomaly Detection with Score functions based on Nearest Neighbor Graphs K. Crammer, A. Kulesza, M. Dredze Adaptive Regularization of Weight Vectors Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu, Z. Yang Adaptive Regularization for Transductive Support Vector Machine J. Luttinen, A. Ilin Variational Gaussian-process factor analysis for modeling spatio-temporal data M. Mozer, H. Pashler, N. Cepeda, R. Lindsey, E. Vul Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory X. Wu, A. So, Z. Li, S. Li Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming S. Huang, J. Li, L. Sun, J. Liu, T. Wu, K. Chen, A. Fleisher, E. Reiman, J. Ye Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data
3:40 - 4:10pm	Break
4:10 - 5:10pm	Oral session 8: Probabilistic Models and KernelsSession Chair:Jon McAuliffe
	J. Chang, J. Boyd-Graber, S. Gerrish, C. Wang, D. Blei Reading Tea Leaves: How Humans Interpret Topic Models E. Fox, E. Sudderth, M. Jordan, A. Willsky Sharing Features among Dynamical Systems with Beta Processes N. Shervashidze, K. Borgwardt Fast Subtree Kernels on Graphs
5:10 - 5:30pm	Spotlights
	S. Venkataraman, A. Blum, D. Song, S. Sen, O. Spatscheck Tracking Dynamic Sources of Malicious Activity at Internet Scale G. Konidaris, A. Barto Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining L. Bo, C. Sminchisescu Efficient Match Kernel between Sets of Features for Visual Recognition A. Fletcher, S. Rangan Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis B. Kulis, T. Darrell Learning to Hash with Binary Reconstructive Embeddings S. Gershman, E. Vul, J. Tenenbaum Perceptual Multistability as Markov Chain Monte Carlo Inference A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright Information-theoretic lower bounds on the oracle complexity of convex optimization K. Heller, A. Sanborn, N. Chater Hierarchical Learning of Dimensional Biases in Human Categorization G. Raskutti, M. Wainwright, B. Yu Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness L. ShiUpdateMe, T. Griffiths Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling J. Graca, K. Ganchev, B. Taskar, F. Pereira Posterior vs Parameter Sparsity in Latent Variable Models I. Stevenson, K. Koerding Structural inference affects depth perception in the context of potential occlusion H. Pirsiavash, D. Ramanan, C. Fowlkes Bilinear classifiers for visual recognition
5:30 - 7:30pm	Dinner Break
7:30 - 11:59pm	Poster Session
	R. Legenstein, S. Chase, A. Schwartz, W. Maass W1 Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning G. Mann, R. McDonald, M. Mohri, N. Silberman, D. Walker W2 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models S. Kumar, M. Mohri, A. Talwalkar W3 Ensemble Nystrom Method N. Singh-Miller, M. Collins W4 Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition P. Germain, A. Lacasse, F. Laviolette, M. Marchand, S. Shanian W5 From PAC-Bayes Bounds to KL Regularization N. Shervashidze, K. Borgwardt W6 Fast subtree kernels on graphs K. Crammer, A. Kulesza, M. Dredze W7 Adaptive Regularization of Weight Vectors Y. Cho, L. Saul W8 Kernel Methods for Deep Learning E. Garcia, M. Gupta W9 Lattice Regression J. Bergstra, Y. Bengio W10 Slow, Decorrelated Features for Pretraining Complex Cell-like Networks A. Fletcher, S. Rangan W11 Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis D. Wipf, S. Nagarajan W12 Sparse Estimation Using General Likelihoods and Non-Factorial Priors J. Duchi, Y. Singer W13 Efficient Learning using Forward-Backward Splitting V. Farias, S. Jagabathula, D. Shah W14 A Data-Driven Approach to Modeling Choice G. Kim, A. Torralba W15 Unsupervised Detection of Regions of Interest Using Iterative Link Analysis S. Turaga, K. Briggman, M. Helmstaedter, W. Denk, H. Seung W16 Maximin affinity learning of image segmentation S. Fidler, M. Boben, A. Leonardis W17 Evaluating multi-class learning strategies in a generative hierarchical framework for object detection F. Sinz, E. Simoncelli, M. Bethge W18 Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions D. Krishnan, R. Fergus W19 Fast Image Deconvolution using Hyper-Laplacian Priors T. Chin, H. Wang, D. Suter W20 The Ordered Residual Kernel for Robust Motion Subspace Clustering S. Gould, T. Gao, D. Koller W21 Region-based Segmentation and Object Detection L. Bo, C. Sminchisescu W22 Efficient Match Kernel between Sets of Features for Visual Recognition B. Russell, A. Efros, J. Sivic, B. Freeman, A. Zisserman W23 Segmenting Scenes by Matching Image Composites I. Stevenson, K. Koerding W24 Structural inference affects depth perception in the context of potential occlusion J. Luo, B. Caputo, V. Ferrari W25 Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation H. Pirsiavash, D. Ramanan, C. Fowlkes W26 Bilinear classifiers for visual recognition P. Berens, S. Gerwinn, A. Ecker, M. Bethge W27 Neurometric function analysis of population codes J. Pillow W28 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models J. Pfister, P. Dayan, M. Lengyel W29 Know Thy Neighbour: A Normative Theory of Synaptic Depression S. Huang, J. Li, L. Sun, J. Liu, T. Wu, K. Chen, A. Fleisher, E. Reiman, J. Ye W30 Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data L. ShiUpdateMe, T. Griffiths W31 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling B. Chai, D. Walther, D. Beck, F. Li W32 Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis C. Kemp W33 Quantification and the language of thought A. Jern, K. Chang, C. Kemp W34 Bayesian Belief Polarization M. Mozer, H. Pashler, N. Cepeda, R. Lindsey, E. Vul W35 Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory S. Gershman, E. Vul, J. Tenenbaum W36 Perceptual Multistability as Markov Chain Monte Carlo Inference H. Yao, R. Sutton, S. Bhatnagar, D. Diao, C. Szepesvari W37 Multi-Step Dyna Planning for Policy Evaluation and Control J. Veness, D. Silver, W. Uther, A. Blair W38 Bootstrapping from Game Tree Search G. Konidaris, A. Barto W39 Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining K. Waugh, N. Bard, M. Bowling W40 Strategy Grafting in Extensive Games M. Allen, S. Zilberstein W41 Complexity of Decentralized Control: Special Cases M. Hutter W42 Discrete MDL Predicts in Total Variation A. Kalai, V. Kanade W43 Potential-Based Agnostic Boosting E. Hazan, S. Kale W44 On Stochastic and Worst-case Models for Investing f. xia, T. Liu, H. Li W45 Statistical Consistency of Top-k Ranking M. Amini, N. Usunier, C. Goutte W46 Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization S. Venkataraman, A. Blum, D. Song, S. Sen, O. Spatscheck W47 Tracking Dynamic Sources of Malicious Activity at Internet Scale B. Sriperumbudur, K. Fukumizu, A. Gretton, G. Lanckriet, B. Schölkopf W48 Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright W49 Information-theoretic lower bounds on the oracle complexity of convex optimization G. Raskutti, M. Wainwright, B. Yu W50 Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness K. Chaudhuri, Y. Freund, D. Hsu W51 A Parameter-free Hedging Algorithm J. Chang, J. Boyd-Graber, S. Gerrish, C. Wang, D. Blei W52 Reading Tea Leaves: How Humans Interpret Topic Models L. Wang W53 Sufficient Conditions for Agnostic Active Learnable Y. Ying, K. Huang, C. Campbell W54 Sparse Metric Learning via Smooth Optimization B. Nadler, N. Srebro, X. Zhou W55 Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data W. Bian, D. Tao W56 Manifold Regularization for SIR with Rate Root-n Convergence M. Zhao, V. Saligrama W57 Anomaly Detection with Score functions based on Nearest Neighbor Graphs Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu, Z. Yang W58 Adaptive Regularization for Transductive Support Vector Machine F. Zhou, F. De la Torre W59 Canonical Time Warping for Alignment of Human Behavior X. Wu, A. So, Z. Li, S. Li W60 Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming R. Salakhutdinov, G. Hinton W61 Replicated Softmax: an Undirected Topic Model S. Rota Bulò, M. Pelillo W62 A Game-Theoretic Approach to Hypergraph Clustering B. Kulis, T. Darrell W63 Learning to Hash with Binary Reconstructive Embeddings J. Graca, K. Ganchev, B. Taskar, F. Pereira W64 Posterior vs Parameter Sparsity in Latent Variable Models J. Lucke, R. Turner, M. Sahani, M. Henniges W65 Occlusive Components Analysis M. Van Gerven, B. Cseke, R. Oostenveld, T. Heskes W66 Bayesian Source Localization with the Multivariate Laplace Prior L. Du, L. Ren, D. Dunson, L. Carin W67 A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation F. Caron, A. Doucet W68 Bayesian Nonparametric Models on Decomposable Graphs C. Zhou, H. Wang, Y. Wang W69 Efficient Moments-based Permutation Tests L. Dietz, V. Dallmeier, A. Zeller, T. Scheffer W70 Localizing Bugs in Program Executions with Graphical Models J. Culpepper, B. Olshausen W71 Learning transport operators for image manifolds J. Luttinen, A. Ilin W72 Variational Gaussian-process factor analysis for modeling spatio-temporal data M. Fromer, A. Globerson W73 An LP View of the M-best MAP problem C. Bejan, M. Titsworth, A. Hickl, S. Harabagiu W74 Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution E. Fox, E. Sudderth, M. Jordan, A. Willsky W75 Sharing Features among Dynamical Systems with Beta Processes N. Quadrianto, T. Caetano, J. Lim, D. Schuurmans W76 Convex Relaxation of Mixture Regression with Efficient Algorithms A. McCallum, K. Schultz, S. Singh W77 FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs A. Ihler, A. Frank, P. Smyth W78 Particle-based Variational Inference for Continuous Systems A. Choi, A. Darwiche W79 Approximating MAP by Compensating for Structural Relaxations B. Moghaddam, B. Marlin, M. Khan, K. Murphy W80 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models A. Courville, D. Eck, Y. Bengio W81 An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism P. Rai, H. Daume III W82 Multi-Label Prediction via Sparse Infinite CCA A. Ozakin, A. Gray W83 Submanifold density estimation X. Yang, S. Kim, E. Xing W84 Heterogeneous multitask learning with joint sparsity constraints H. Lu, M. Weiden, A. Yuille W85 Modeling the spacing effect in sequential category learning K. Heller, A. Sanborn, N. Chater W86 Hierarchical Learning of Dimensional Biases in Human Categorization T. Ullman, C. Baker, O. Macindoe, O. Evans, N. Goodman, J. Tenenbaum W87 Help or Hinder: Bayesian Models of Social Goal Inference
7:30 - 11:59pm	Demonstrations
	H. Cadambi An FPGA-based Multi-Algorithm Learning and Classification Engine A. Gupta Curious George: An Attentive Semantic Robotic Vision System M. Park Deformed Lattice Detection in Real-World Images Using a Novel Mean-Shift Belief V. Mansinghka Monte: An Interactive Ssytem for Massively Parallel Probabilistic Programming C. Eliasmith Nengo: Large-Scale Integrated Neural Modeling B. Kveton Real-Time Adaptive Face Recognition C. Maina Robust Speaker Recognition Using Approximate Bayesian Inference
Thursday, December 10
7:30 - 9:00am	Breakfast
8:00 - 11:00am	Registration Desk
8:00am - 12:00pm	Internet Cafe
8:30 - 9:50am	Oral session 9: Bayesian AnalysisSession Chair:Erik B Sudderth
	Persi Diaconis Bayesian Analysis of Markov Chains B. Moghaddam, B. Marlin, M. Khan, K. Murphy Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models
9:50 - 10:30am	Break
10:30 - 11:50am	Oral session 10: Neural Modeling and ImagingSession Chair:Arthur Gretton
	J. Pillow Time-rescaling Methods for the Estimation and Assessment of Non-Poisson Neural Encoding Models Karl Deisseroth Optogenetics: Development and Application
11:50am - 1:30pm	Lunch Break
1:30 - 4:30pm	Mini Symposia
	F. Perez-Cruz, E. Parrado-Hernandez, D. Hardoon, J. Madrid-Sanchez Assistive Machine Learning for People with Disabilities F. Popescu, I. Guyon, G. Nolte Causality and Time Series Analysis J. Kolter, T. Dietterich, A. Ng Machine Learning for Sustainability J. Vert, Y. Qi, G. Chechik, A. Zien, T. Hertz, W. Noble Machine Learning in Computational Biology M. Hutter, W. Uther, P. Poupart Partially Observable Reinforcement Learning
2:50 - 3:10pm	Break

Workshops (December 11-12, 2009)

Each workshop generally has a break from 10:30AM until 3:30PM. For more workshop schedule information please consult the Workshop URL on the workshop's page.

Thursday, December 10
5:00 - 8:30pm	Registration Desk
9:30 - 9:40pm	Richard Zemel Opening Remarks
9:40 - 10:30pm	Simon Haykin Cognitive Dynamic Radio
Friday, December 11
6:30 - 8:00am	Breakfast
7:00 - 11:00am	Registration Desk
7:30am - 6:30pm	Rui M Castro, Nando de Freitas, Ruben Martinez-Cantin Adaptive Sensing, Active Learning, and Experimental Design
7:30am - 6:30pm	Shivani Agarwal, Chris J Burges, Koby Crammer Advances in Ranking
7:30am - 6:30pm	Edoardo M Airoldi, Jure Leskovec, Jon Kleinberg, Josh Tenenbaum Analyzing Networks and Learning With Graphs
7:30am - 6:30pm	David Blei, Jordan Boyd-Graber, Jonathan Chang, Katherine A Heller, Hanna M Wallach Applications for Topic Models: Text and Beyond
7:30am - 6:30pm	Margareta Ackerman, Shai Ben-David, Avrim Blum, Isabelle Guyon, Ulrike von Luxburg, Robert C Williamson, Reza Bosagh Zadeh Clustering: Science or art? Towards principled approaches
7:30am - 6:30pm	Andreas Krause, Pradeep K Ravikumar, Jeff A Bilmes Discrete Optimization in Machine Learning: Submodularity, Polyhedra and Sparsity
7:30am - 6:30pm	Alex Clark, Dorota Glowacka, John S Shawe-Taylor, Yee Whye Teh, Chris J Watkins Grammar Induction, Representation of Language and Language Learning
7:30am - 6:30pm	Alexander Gray, Alexander J Smola, Arthur Gretton, Joseph E Gonzalez, Carlos Guestrin Large-Scale Machine Learning: Parallelism and Massive Datasets
7:30am - 6:30pm	Gal Chechik, Tomer Hertz, William S Noble, Yanjun Qi, Jean-Philippe Vert, Alexander Zien Machine Learning in Computational Biology
7:30am - 6:30pm	Jean-Pascal Pfister, Máté Lengyel Normative electrophysiology: Explaining cellular properties of neurons from first principles
7:30am - 6:30pm	Marc P Deisenroth, Hilbert J Kappen, Emo Todorov, Duy Nguyen-Tuong, Carl Edward Rasmussen, Jan R Peters Probabilistic Approaches for Control and Robotics
7:30am - 6:30pm	Guy Lebanon, Fei Sha Statistical Machine Learning for Visual Analytics
7:30am - 6:30pm	Simon Haykin, Terrence J Sejnowski, Steven Zucker The Curse of Dimensionality Problem: How Can the Brain Solve It?
7:30am - 6:30pm	Gert Lanckriet, Brian McFee, Francis Bach, Nati Srebro Understanding Multiple Kernel Learning Methods
9:00 - 9:30am	Coffee Break
3:30 - 6:45pm	Registration Desk
5:00 - 5:30pm	Coffee Break
Saturday, December 12
6:30 - 8:00am	Breakfast
7:00 - 11:00am	Registration Desk
7:30am - 6:30pm	Sumit Basu, Ashish Kapoor Analysis and Design of Algorithms for Interactive Machine Learning
7:30am - 6:30pm	Ruslan R Salakhutdinov, Amir Globerson, David Sontag Approximate Learning of Large Scale Graphical Models
7:30am - 6:30pm	Noah Goodman, Edward Vul, Tom Griffiths, Josh Tenenbaum Bounded-rational analyses of human cognition: Bayesian models, approximate inference, and the brain
7:30am - 6:30pm	Li Deng, Dong Yu, Geoffrey E Hinton Deep Learning for Speech Recognition and Related Applications
7:30am - 6:30pm	Mauricio A Alvarez, Lorenzo Rosasco, Neil D Lawrence Kernels for Multiple Outputs and Multi-task Learning: Frequentist and Bayesian Points of View
7:30am - 6:30pm	Barbara Caputo, Nicolo Cesa-Bianchi, David R Hardoon, Gayle Leen, Francesco Orabona, Jaakko Peltonen, Simon Rogers Learning from Multiple Sources with Applications to Robotics
7:30am - 6:30pm	Tiberio Caetano, Carlos Guestrin, Jonathan Huang, Risi Kondor, Guy Lebanon, Marina Meila Learning with Orderings
7:30am - 6:30pm	Richard Baraniuk, Volkan Cevher, Mark A Davenport, Piotr Indyk, Bruno A Olshausen, Michael B Wakin Manifolds, sparsity, and structured models: When can low-dimensional geometry really help?
7:30am - 6:30pm	Dilan Gorur, Francois Caron, Yee Whye Teh, David B Dunson, Zoubin Ghahramani, Michael I Jordan Nonparametric Bayes
7:30am - 6:30pm	Sebastian Nowozin, Suvrit Sra, S.V.N Vishwanthan, Stephen Wright Optimization for Machine Learning
7:30am - 6:30pm	Sinno Jialin Pan, Ivor W Tsang, Le Song, Karsten Borgwardt, Qiang Yang Transfer Learning for Structured Data
7:30am - 6:45pm	Stephane Canu, Olivier Cappe, Arthur Gretton, Zaid Harchaoui, Alain Rakotomamonjy, Jean-Philippe Vert Temporal Segmentation: Perspectives from Statistics, Machine Learning, and Signal Processing
7:30am - 7:00pm	Simon Lacoste-Julien, Percy S Liang, Guillaume Bouchard The Generative and Discriminative Learning Interface
7:30am - 10:00pm	Karl Friston, Moritz Grosse-Wentrup, Uta Noppeney, Bernhard Schölkopf Connectivity Inference in Neuroimaging
9:00 - 9:30am	Coffee Break
3:30 - 6:45pm	Registration Desk
5:00 - 5:30pm	Coffee Break
7:00 - 10:00pm	Banquet

The schedule was last modified on 2012-12-2 13:55 PST