Schedule

Tutorials (December 6, 2010)

Sunday, December 5
4:00 - 8:00pm	Registration Desk
Monday, December 6
8:00am - 6:00pm	Internet Cafe
8:00am - 6:00pm	Registration Desk
9:30 - 11:30am	Peter Bühlmann High-dimensional Statistics: Prediction, Association and Causal Inference
9:30 - 11:30am	Dana Ballard Reinforcement Learning for Embodied Cognition
1:00 - 3:00pm	Stephen Wright Optimization Algorithms in Machine Learning
1:00 - 3:00pm	Nathaniel Daw Reinforcement Learning in Humans and Other Animals
3:30 - 5:30pm	Peter Hoff Latent Factor Models for Relational Arrays and Network Data
3:30 - 5:30pm	Stefano Soatto Vision-Based Control, Control-Based Vision, and the Information Knot That Ties Them

Conference Sessions (December 6-9, 2010)

Monday, December 6
6:15 - 6:30pm	Terrence Sejnowski, Richard Zemel, John Shawe-Taylor Opening Remarks and Awards
6:30 - 6:55pm	Spotlights Session 1Session Chair:Xiaojin (Jerry) Zhu
	L. Jie, F. Orabona Learning from Candidate Labeling Sets L. Maurits, D. Navarro, A. Perfors Why are some word orders more common than others? A uniform information density account D. Sun, E. Sudderth, M. Black Layered image motion with explicit occlusions, temporal consistency, and depth ordering P. Li, A. König, W. Gui b-Bit Minwise Hashing for Estimating Three-Way Similarities U. von Luxburg, A. Radl, M. Hein Getting lost in space: Large sample analysis of the resistance distance
7:00 - 11:59pm	Poster Session and Reception
	H. Zhou, Q. Cheng M1 Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework N. Quadrianto, A. Smola, T. Caetano, S. Vishwanathan, J. Petterson M2 Multitask Learning without Label Correspondences Y. Noh, B. Zhang, D. Lee M3 Generative Local Metric Learning for Nearest Neighbor Classification R. Memisevic, C. Zach, G. Hinton, M. Pollefeys M4 Gated Softmax Classification F. Li, C. Sminchisescu M5 Convex Multiple-Instance Learning by Estimating Likelihood Ratio M. Saberian, N. Vasconcelos M6 Boosting Classifier Cascades A. Kundu, V. Tankasali, C. Bhattacharyya, A. Ben-Tal M7 Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions K. Gai, G. Chen, C. Zhang M8 Learning Kernels with Radiuses of Minimum Enclosing Balls S. Bucak, R. Jin, A. Jain M9 Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition E. De Vito, L. Rosasco, A. Toigo M10 Spectral Regularization for Support Estimation D. McAllester, T. Hazan, J. Keshet M11 Direct Loss Minimization for Structured Prediction D. Weiss, B. Sapp, B. Taskar M12 Sidestepping Intractable Inference with Structured Ensemble Cascades G. Montavon, M. Braun, K. Muller M13 Layer-wise analysis of deep networks with Gaussian kernels O. Maillard, R. Munos M14 Scrambled Objects for Least-Squares Regression A. Lozano, V. Sindhwani M15 Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference L. Maurits, D. Navarro, A. Perfors M16 Why are some word orders more common than others? A uniform information density account S. Filippi, O. Cappe, A. Garivier, C. Szepesvari M17 Parametric Bandits: The Generalized Linear Case J. Schmiedt, C. Albers, K. Pawelzik M18 Spike timing-dependent plasticity as dynamic filter S. Ganguli, H. Sompolinsky M19 Short-term memory in neuronal networks through dynamical compressed sensing D. Reichert, P. Series, A. Storkey M20 Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model E. Corbett, E. Perreault, K. Koerding M21 Mixture of time-warped trajectory models for movement decoding Y. Liu, M. Sharma, C. Gaona, J. Breshears, j. Roland, z. Freudenburg, K. Weinberger, E. Leuthardt M22 Decoding Ipsilateral Finger Movements from ECoG Signals in Humans P. Li, A. König, W. Gui M23 b-Bit Minwise Hashing for Estimating Three-Way Similarities A. Fern, P. Tadepalli M24 A Computational Decision Theory for Interactive Assistants J. Liu, P. Wonka, J. Ye M25 Multi-Stage Dantzig Selector D. Pal, B. Poczos, C. Szepesvari M26 Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs P. Jones, V. Saligrama, S. Mitter M27 Probabilistic Belief Revision with Structural Constraints U. von Luxburg, A. Radl, M. Hein M28 Getting lost in space: Large sample analysis of the resistance distance A. Jiang, K. Leyton-Brown M29 Bayesian Action-Graph Games A. Kleiner, a. rahimi, M. Jordan M30 Random Conic Pursuit for Semidefinite Programming V. Kolmogorov M31 Generalized roof duality and bisubmodular functions K. Scheinberg, S. Ma, D. Goldfarb M32 Sparse Inverse Covariance Selection via Alternating Linearization Methods G. Leung, N. Quadrianto, A. Smola, K. Tsioutsiouliklis M33 Optimal Web-Scale Tiering as a Flow Problem M. Zinkevich, M. Weimer, A. Smola, L. Li M34 Parallelized Stochastic Gradient Descent S. Kale, L. Reyzin, R. Schapire M35 Non-Stochastic Bandit Slate Problems J. Abernethy, M. Warmuth M36 Repeated Games against Budgeted Adversaries W. Chen, T. Liu, Z. Ma M37 Two-Layer Generalization Analysis for Ranking Using Rademacher Average T. Peel, S. Anthoine, L. Ralaivola M38 Empirical Bernstein Inequalities for U-Statistics D. Pechyony, V. Vapnik M39 On the Theory of Learnining with Privileged Information M. White, A. White M40 Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains D. Silver, J. Veness M41 Monte-Carlo Planning in Large POMDPs S. Mahadevan, B. LIU M42 Basis Construction from Power Series Expansions of Value Functions J. Sorg, S. Singh, R. Lewis M43 Reward Design via Online Gradient Ascent A. Boularias, B. Chaib-draa M44 Bootstrapping Apprenticeship Learning M. Milani Fard, J. Pineau M45 PAC-Bayesian Model Selection for Reinforcement Learning K. Rawlik, M. Toussaint, S. Vijayakumar M46 An Approximate Inference Approach to Temporal Optimization in Optimal Control F. Doshi-Velez, D. Wingate, N. Roy, J. Tenenbaum M47 Nonparametric Bayesian Policy Priors for Reinforcement Learning B. Boots, G. Gordon M48 Predictive State Temporal Difference Learning H. van Hasselt M49 Double Q-learning A. Farahmand, R. Munos, C. Szepesvari M50 Error Propagation for Approximate Policy and Value Iteration M. Pathak, S. Rane, B. Raj M51 Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers T. Qin, X. Geng, T. Liu M52 A New Probabilistic Model for Rank Aggregation J. Puertas, J. Bornschein, J. Lucke M53 The Maximal Causes of Natural Scenes are Edge Filters D. Bickson, C. Guestrin M54 Inference with Multivariate Heavy-Tails in Linear Models S. Bach, M. Maloof M55 A Bayesian Approach to Concept Drift C. Barber, J. Bockhorst, P. Roebber M56 Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting K. Takiyama, M. Okada M57 Switching state space model for simultaneously estimating state transitions and nonstationary firing rates M. Broecheler, L. Getoor M58 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning F. Wauthier, M. Jordan M59 Heavy-Tailed Process Priors for Selective Shrinkage A. Kumar, S. Zilberstein M60 MAP Estimation for Graphical Models by Likelihood Maximization H. Liu, K. Roeder, L. Wasserman M61 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models B. Thiesson, C. Wang M62 Fast Large-scale Mixture Modeling with Component-specific Data Partitions I. Sato, K. Kurihara, H. Nakagawa M63 Deterministic Single-Pass Algorithm for LDA N. Lao, J. Zhu, L. Xinwang, Y. Liu, W. Cohen M64 Efficient Relational Learning with Hidden Variable Detection J. Vert, K. Bleakley M65 Fast detection of multiple change-points shared by many signals using group LARS S. Millner, A. Grübl, K. Meier, J. Schemmel, M. Schwartz M66 A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model N. Jojic, A. Perina, V. Murino M67 Structural epitome: a way to summarize one’s visual experience S. Wu, X. He, H. Lu, A. Yuille M68 A unified model of short-range and long-range motion perception L. Li, H. Su, E. Xing, F. Li M69 Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification M. Fritz, K. Saenko, T. Darrell M70 Size Matters: Metric Visual Search Constraints from Monocular Metadata A. Ayvaci, M. Raptis, S. Soatto M71 Occlusion Detection and Motion Estimation with Convex Optimization H. Lu, T. Lin, A. Lee, L. Vese, A. Yuille M72 Functional form of motion priors in human motion perception D. Sun, E. Sudderth, M. Black M73 Layered image motion with explicit occlusions, temporal consistency, and depth ordering F. Agakov, P. McKeigue, J. Krohn, A. Storkey M74 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies L. Huang, J. Jia, B. Yu, B. Chun, P. Maniatis, M. Naik M75 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression H. Le, Z. Bar-Joseph M76 Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings S. Lee, J. Zhu, E. Xing M77 Adaptive Multi-Task Lasso: with Application to eQTL Detection J. Petterson, T. Caetano M78 Reverse Multi-Label Learning S. Cohen, N. Smith M79 Empirical Risk Minimization with Approximations of Probabilistic Grammars P. Ruvolo, j. movellan M80 An Alternative to Low-level-Sychrony-Based Methods for Speech Detection G. Dahl, M. Ranzato, A. Mohamed, G. Hinton M81 Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine T. Lan, Y. Wang, W. Yang, G. Mori M82 Beyond Actions: Discriminative Models for Contextual Group Activities P. Garrigues, B. Olshausen M83 Group Sparse Coding with a Laplacian Scale Mixture Prior D. Kingma, Y. LeCun M84 Regularized estimation of image statistics by Score Matching L. Jie, F. Orabona M85 Learning from Candidate Labeling Sets H. Daume III, A. Kumar, A. Saha M86 Co-regularization Based Semi-supervised Domain Adaptation J. Azimi, A. Fern, X. Fern M87 Batch Bayesian Optimization via Simulation Matching C. Sawade, N. Landwehr, T. Scheffer M88 Active Estimation of F-Measures A. Beygelzimer, D. Hsu, J. Langford, T. Zhang M89 Agnostic Active Learning Without Constraints J. Bien, Y. Xu, M. Mahoney M90 CUR from a Sparse Optimization Viewpoint M. Ackerman, S. Ben-David, D. Loker M91 Towards Property-Based Classification of Clustering Paradigms J. Kolter, S. Batra, A. Ng M92 Energy Disaggregation via Discriminative Sparse Coding
Tuesday, December 7
7:30 - 9:00am	Breakfast
8:00 - 9:00am	Breakfast
8:00am - 6:00pm	Internet Cafe
8:00am - 6:00pm	Registration Desk
8:30 - 9:40am	Oral Session 1Session Chair:Bill Triggs
	Antonio Rangel How Does the Brain Compute and Compare Values at the Time of Decision-Making? S. Druckmann, D. Chklovskii Over-complete representations on recurrent neural networks can support persistent percepts
9:40 - 10:00am	Spotlights Session 2Session Chair:Bill Triggs
	M. Mozer, H. Pashler, M. Wilder, R. Lindsey, M. Jones, M. Jones Improving Human Judgments by Decontaminating Sequential Dependencies D. Goodman, R. Brette Learning to localise sounds with spiking neural networks S. Chevallier, H. Paugam-Moisy, M. Sebag SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system C. Fung, K. Wong, H. Wang, S. Wu Attractor Dynamics with Synaptic Depression
10:00 - 10:20am	Oral Session 2Session Chair:Lee Sun
	P. Shenoy, R. Rao, A. Yu A rational decision making framework for inhibitory control
10:20 - 10:50am	Break
10:50 - 11:10am	Oral Session 3Session Chair:Ben Taskar
	I. Mukherjee, R. Schapire A Theory of Multiclass Boosting
11:10 - 11:30am	Spotlights Session 3Session Chair:Ben Taskar
	A. Wilson, Z. Ghahramani Copula Processes K. Muralidharan, N. Vasconcelos A biologically plausible network for the computation of orientation dominance k. kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, Y. LeCun Learning Convolutional Feature Hierarchies for Visual Recognition M. Ghavamzadeh, A. Lazaric, O. Maillard, R. Munos LSTD with Random Projections
11:30 - 11:50am	Oral Session 4Session Chair:Ofer Dekel
	A. Rakhlin, K. Sridharan, A. Tewari Online Learning: Random Averages, Combinatorial Parameters, and Learnability
11:50am - 12:10pm	Spotlights Session 4Session Chair:Ofer Dekel
	L. Bo, X. Ren, D. Fox Kernel Descriptors for Visual Recognition K. Nagano, Y. Kawahara, S. Iwata Minimum Average Cost Clustering A. Lazar, Y. Slutskiy Identifying Dendritic Processing O. Williams, F. McSherry Probabilistic Inference and Differential Privacy
12:10 - 2:00pm	Lunch
2:00 - 3:10pm	Oral Session 5Session Chair:Iain Murray
	Xiao-Li Meng Machine Learning with Human Intelligence: Principled Corner Cutting (PC2) A. Agarwal, S. Negahban, M. Wainwright Fast global convergence rates of gradient methods for high-dimensional statistical recovery
3:10 - 3:30pm	Spotlights Session 5Session Chair:Iain Murray
	A. Sayedi, A. Blum, M. Zadimoghaddam Trading off Mistakes and Don't-Know Predictions M. Urry, P. Sollich Exact learning curves for Gaussian process regression on large random graphs M. Johnson, K. Demuth, M. Frank, B. Jones Synergies in learning words and their referents A. Chambers, P. Smyth, M. Steyvers Learning concept graphs from text with stick-breaking priors
3:30 - 3:50pm	Oral Session 6Session Chair:Matthias Seeger
	F. Bach Structured sparsity-inducing norms through submodular functions
3:50 - 4:20pm	Break
4:20 - 5:00pm	Oral Session 7Session Chair:Raquel Urtasun
	U. Syed, B. Taskar Semi-Supervised Learning with Adversarially Missing Label Information S. Jakkam Reddi, S. Sarawagi, S. Vishwanathan MAP estimation in Binary MRFs via Bipartite Multi-cuts
5:00 - 5:20pm	Spotlights Session 6Session Chair:Raquel Urtasun
	P. Stobbe, A. Krause Efficient Minimization of Decomposable Submodular Functions M. Vinyals, J. Cerquides, A. Farinelli, J. Rodríguez-Aguilar Worst-case bounds on the quality of max-product fixed-points V. Lempitsky, A. Zisserman Learning To Count Objects in Images J. Austerweil, T. Griffiths Learning invariant features using the Transformed Indian Buffet Process
5:20 - 5:40pm	Oral Session 8Session Chair:Rich Caruana
	A. Jalali, P. Ravikumar, S. Sanghavi, C. Ruan A Dirty Model for Multi-task Learning
5:40 - 6:00pm	Spotlights Session 7Session Chair:Rich Caruana
	S. Vishwanathan, Z. sun, N. Ampornpunt, M. Varma Multiple Kernel Learning and the SMO Algorithm A. Bouchard-Côté, M. Jordan Variational Inference over Combinatorial Spaces P. Jain, B. Kulis, I. Dhillon Inductive Regularized Learning of Kernel Functions D. Pfau, N. Bartlett, F. Wood Probabilistic Deterministic Infinite Automata
7:00 - 11:59pm	Poster Session
	K. Rajan, L. Abbott, H. Sompolinsky T1 Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics K. Li, L. Guo, C. Faraco, D. Zhu, F. Deng, T. Zhang, X. Jiang, D. Zhang, H. Chen, X. Hu, S. Miller, t. Liu T2 Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles D. Lashkari, R. Sridharan, P. Golland T3 Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations A. Singh, R. Jolivet, P. Magistretti, B. Weber T4 Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models A. Lazar, Y. Slutskiy T5 Identifying Dendritic Processing C. Fung, K. Wong, H. Wang, S. Wu T6 Attractor Dynamics with Synaptic Depression P. Shenoy, R. Rao, A. Yu T7 A rational decision making framework for inhibitory control S. Gershman, R. Wilson T8 The Neural Costs of Optimal Control S. Druckmann, D. Chklovskii T9 Over-complete representations on recurrent neural networks can support persistent percepts F. Gerhard, W. Gerstner T10 Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models S. Lyu T11 Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform R. Haefner, M. Bethge T12 Evaluating neuronal codes for inference using Fisher information D. Navarro T13 Learning the context of a category Y. Xu, C. Kemp T14 Inference and communication in the game of Password C. Cortes, Y. Mansour, M. Mohri T15 Learning Bounds for Importance Weighting N. Srebro, K. Sridharan, A. Tewari T16 Smoothness, Low Noise and Fast Rates A. Rakhlin, K. Sridharan, A. Tewari T17 Online Learning: Random Averages, Combinatorial Parameters, and Learnability E. Mizutani, S. Dreyfus T18 An analysis on negative curvature induced by singularity in multi-layer neural-network learning A. Sayedi, M. Zadimoghaddam, A. Blum T19 Trading off Mistakes and Don't-Know Predictions A. Agarwal, S. Negahban, M. Wainwright T20 Fast global convergence rates of gradient methods for high-dimensional statistical recovery A. Jalali, P. Ravikumar, S. Sanghavi, C. Ruan T21 A Dirty Model for Multi-task Learning H. Masnadi-Shirazi, N. Vasconcelos T22 Variable margin losses for classifier design H. Xu, C. Caramanis, S. Sanghavi T23 Robust PCA via Outlier Pursuit J. Mairal, R. Jenatton, G. Obozinski, F. Bach T24 Network Flow Algorithms for Structured Sparsity P. Stobbe, A. Krause T25 Efficient Minimization of Decomposable Submodular Functions K. Nagano, Y. Kawahara, S. Iwata T26 Minimum Average Cost Clustering J. Lee, B. Recht, R. Salakhutdinov, N. Srebro, J. Tropp T27 Practical Large-Scale Optimization for Max-norm Regularization J. Austerweil, T. Griffiths T28 Learning invariant features using the Transformed Indian Buffet Process M. Johnson, K. Demuth, M. Frank, B. Jones T29 Synergies in learning words and their referents M. Magdon-Ismail T30 Permutation Complexity Bound on Out-Sample Error G. Blanchard, N. Krämer T31 Optimal learning rates for Kernel Conjugate Gradient regression L. Hannah, W. Powell, D. Blei T32 Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable C. Li, A. Kowdle, A. Saxena, T. Chen T33 Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models V. Lempitsky, A. Zisserman T34 Learning To Count Objects in Images K. Muralidharan, N. Vasconcelos T35 A biologically plausible network for the computation of orientation dominance G. Taylor, R. Fergus, G. Williams, I. Spiro, C. Bregler T36 Pose-Sensitive Embedding by Nonlinear NCA Regression M. Salzmann, R. Urtasun T37 Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation K. Mitra, S. Sheorey, R. Chellappa T38 Large-Scale Matrix Factorization with Missing Data under Additional Constraints N. Payet, S. Todorovic T39 (RF)^2 -- Random Forest Random Field L. Bo, X. Ren, D. Fox T40 Kernel Descriptors for Visual Recognition A. Bergamo, L. Torresani T41 Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach V. Froyen, J. Feldman, M. Singh T42 A Bayesian Framework for Figure-Ground Interpretation U. Syed, B. Taskar T43 Semi-Supervised Learning with Adversarially Missing Label Information M. Kumar, B. Packer, D. Koller T44 Self-Paced Learning for Latent Variable Models C. Boutsidis, A. Zouzias, P. Drineas T45 Random Projections for $k$-means Clustering R. Gomes, A. Krause, P. Perona T46 Discriminative Clustering by Regularized Information Maximization A. Goldberg, X. Zhu, B. Recht, J. Sui, R. Nowak T47 Transduction with Matrix Completion: Three Birds with One Stone Q. Le, J. Ngiam, Z. Chen, D. Chia, P. Koh, A. Ng T48 Tiled convolutional neural networks W. Wang, Z. Zhou T49 Multi-View Active Learning in the Non-Realizable Case D. Golovin, A. Krause, D. Ray T50 Near-Optimal Bayesian Active Learning with Noisy Observations P. Jain, S. Vijayanarasimhan, K. Grauman T51 Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning M. Wang, F. Sha, M. Jordan T52 Unsupervised Kernel Dimension Reduction S. Parameswaran, K. Weinberger T53 Large Margin Multi-Task Metric Learning Y. Lin, T. Zhang, S. Zhu, K. Yu T54 Deep Coding Network P. Jain, B. Kulis, I. Dhillon T55 Inductive Regularized Learning of Kernel Functions A. Chambers, P. Smyth, M. Steyvers T56 Learning concept graphs from text with stick-breaking priors E. Wang, D. Liu, J. Silva, D. Dunson, L. Carin T57 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents N. Chen, J. Zhu, E. Xing T58 Predictive Subspace Learning for Multi-view Data: a Large Margin Approach M. Ghavamzadeh, A. Lazaric, O. Maillard, R. Munos T59 LSTD with Random Projections G. Konidaris, S. Kuindersma, A. Barto, R. Grupen T60 Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories Y. Han, Q. Tao, J. Wang T61 Avoiding False Positive in Multi-Instance Learning I. Mukherjee, R. Schapire T62 A Theory of Multiclass Boosting L. Lefakis, F. Fleuret T63 Joint Cascade Optimization Using A Product Of Boosted Classifiers S. Vishwanathan, Z. sun, N. Ampornpunt, M. Varma T64 Multiple Kernel Learning and the SMO Algorithm Y. Yu, M. Yang, L. Xu, M. White, D. Schuurmans T65 Relaxed Clipping: A Global Training Method for Robust Regression and Classification R. Luss, S. Rosset, M. Shahar T66 Decomposing Isotonic Regression for Efficiently Solving Large Problems Y. Jia, M. Salzmann, T. Darrell T67 Factorized Latent Spaces with Structured Sparsity C. Su, S. Srihari T68 Evaluation of Rarity of Fingerprints in Forensics F. Bach T69 Structured sparsity-inducing norms through submodular functions k. kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, Y. LeCun T70 Learning Convolutional Feature Hierarchies for Visual Recognition Y. Zhang, D. Yeung, Q. Xu T71 Probabilistic Multi-Task Feature Selection O. Williams, F. McSherry T72 Probabilistic Inference and Differential Privacy D. Husmeier, F. Dondelinger, S. Lebre T73 Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks A. Bouchard-Côté, M. Jordan T74 Variational Inference over Combinatorial Spaces M. Vinyals, J. Cerquides, A. Farinelli, J. Rodríguez-Aguilar T75 Worst-case bounds on the quality of max-product fixed-points Y. Sun, F. Gomez, J. Schmidhuber T76 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices G. Papandreou, A. Yuille T77 Gaussian sampling by local perturbations D. Lowd, P. Domingos T78 Approximate Inference by Compilation to Arithmetic Circuits S. Jakkam Reddi, S. Sarawagi, S. Vishwanathan T79 MAP estimation in Binary MRFs via Bipartite Multi-cuts J. Gasthaus, Y. Teh T80 Improvements to the Sequence Memoizer D. Pfau, N. Bartlett, F. Wood T81 Probabilistic Deterministic Infinite Automata A. Wilson, Z. Ghahramani T82 Copula Processes A. Chiuso, G. Pillonetto T83 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors M. Urry, P. Sollich T84 Exact learning curves for Gaussian process regression on large random graphs B. Miller, N. Bliss, P. Wolfe T85 Subgraph Detection Using Eigenvector L1 Norms E. Bonilla, S. Guo, S. Sanner T86 Gaussian Process Preference Elicitation J. Domke T87 Implicit Differentiation by Perturbation T. Hazan, R. Urtasun T88 A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction R. Foygel, M. Drton T89 Extended Bayesian Information Criteria for Gaussian Graphical Models T. Claassen, T. Heskes T90 Causal discovery in multiple models from different experiments A. Jha, V. Gogate, A. Meliou, D. Suciu T91 Lifted Inference Seen from the Other Side : The Tractable Features S. Chiappa, J. Peters T92 Movement extraction by detecting dynamics switches and repetitions J. Wiens, J. Guttag T93 Active Learning Applied to Patient-Adaptive Heartbeat Classification N. Karampatziakis T94 Static Analysis of Binary Executables Using Structural SVMs D. Hu, L. van der Maaten, Y. Cho, L. Saul, S. Lerner T95 Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development E. Richard, N. Baskiotis, T. Evgeniou, N. Vayatis T96 Link Discovery using Graph Feature Tracking N. Arora, S. Russell, P. Kidwell, E. Sudderth T97 Global seismic monitoring as probabilistic inference M. Mozer, H. Pashler, M. Wilder, R. Lindsey, M. Jones, M. Jones T98 Improving Human Judgments by Decontaminating Sequential Dependencies S. Chevallier, H. Paugam-Moisy, M. Sebag T99 SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system D. Goodman, R. Brette T100 Learning to localise sounds with spiking neural networks
7:30 - 11:59pm	Demonstrations
	D. Chichkov A framework for evaluating and designing 'attention mechanism' implementations based on tracking of human eye movements M. Prasad Haptic Information Presentation Through Vibro Tactile J. Turian MetaOptimize: A Q+A site for machine learning C. Ong mldata.org - machine learning data and benchmark Y. LeCun NeuFlow: a dataflow processor for convolutional nets and other real-time algorithms J. Van Gael Project Emporia: News Recommendation using Graphical Models
Wednesday, December 8
7:30 - 9:00am	Breakfast
8:00 - 9:00am	Breakfast
8:00am - 6:00pm	Internet Cafe
8:00am - 6:00pm	Registration Desk
8:30 - 9:40am	Oral Session 9Session Chair:Pascal Poupart
	David Parkes The Interplay of Machine Learning and Mechanism Design J. Johns, C. Painter-Wakefield, R. Parr Linear Complementarity for Regularized Policy Evaluation and Improvement
9:40 - 10:00am	Spotlights Session 8Session Chair:Pascal Poupart
	P. Viappiani, C. Boutilier Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets A. Bernstein, S. Mannor, N. Shimkin Online Classification with Specificity Constraints J. Huang, N. Jojic, C. Meek Exact inference and learning for cumulative distribution functions on loopy graphs S. Nakajima, M. Sugiyama, R. Tomioka Global Analytic Solution for Variational Bayesian Matrix Factorization
10:00 - 10:20am	Oral Session 10Session Chair:Fei Fei Li
	P. Welinder, S. Branson, S. Belongie, P. Perona The Multidimensional Wisdom of Crowds
10:20 - 10:50am	Break
10:50 - 11:10am	Oral Session 11Session Chair:Katherine Heller
	D. Lin, E. Grimson, J. Fisher Construction of Dependent Dirichlet Processes based on Poisson Processes
11:10 - 11:30am	Spotlights Session 9Session Chair:Katherine Heller
	U. Dick, P. Haider, T. Scheffer Throttling Poisson Processes H. Liu, X. Chen, J. Lafferty, L. Wasserman Graph-Valued Regression M. Alvarez, J. Peters, B. Schölkopf, N. Lawrence Switched Latent Force Models for Movement Segmentation G. Neu, A. György, A. Antos, C. Szepesvari Online Markov Decision Processes under Bandit Feedback
11:30 - 11:50am	Oral Session 12Session Chair:Nando de Freitas
	I. Murray, R. Adams Slice sampling covariance hyperparameters of latent Gaussian models
11:50am - 12:10pm	Spotlights Session 10Session Chair:Nando de Freitas
	J. Duchi, A. Agarwal, M. Wainwright Distributed Dual Averaging In Networks C. Micchelli, J. Morales, M. Pontil A Family of Penalty Functions for Structured Sparsity P. Jain, R. Meka, I. Dhillon Guaranteed Rank Minimization via Singular Value Projection M. Hoffman, D. Blei, F. Bach Online Learning for Latent Dirichlet Allocation
12:10 - 2:00pm	Lunch
2:00 - 3:10pm	Oral Session 13Session Chair:Nati Srebro
	M. Jordan Statistical Inference of Protein Structure and Function R. Adams, Z. Ghahramani, M. Jordan Tree-Structured Stick Breaking for Hierarchical Data
3:10 - 3:30pm	Spotlights Session 11Session Chair:Nati Srebro
	A. Kulesza, B. Taskar Structured Determinantal Point Processes P. Awasthi, R. Bosagh Zadeh Supervised Clustering U. Shalit, D. Weinshall, G. Chechik Online Learning in The Manifold of Low-Rank Matrices H. Narayanan, S. Mitter Sample Complexity of Testing the Manifold Hypothesis
3:30 - 3:50pm	Oral Session 14Session Chair:Pradeep Ravikumar
	J. Sharpnack, A. Singh Identifying graph-structured activation patterns in networks
3:50 - 4:20pm	Break
4:20 - 5:00pm	Oral Session 15Session Chair:Irina Rish
	F. Triefenbach, A. Jalalvand, B. Schrauwen, J. Martens Phoneme Recognition with Large Hierarchical Reservoirs Z. Syed, J. Guttag Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
5:00 - 5:20pm	Spotlights Session 12Session Chair:Irina Rish
	G. Langs, Y. Tie, L. Rigolo, A. Golby, P. Golland Functional Geometry Alignment and Localization of Brain Areas K. Motwani, N. Adluru, C. Hinrichs, V. Singh Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures J. Tang, P. Abbeel On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient B. Frigyik, M. Gupta, Y. Chen Shadow Dirichlet for Restricted Probability Modeling
5:20 - 5:40pm	Oral Session 16Session Chair:Kilian Weinberger
	S. Myers, J. Leskovec On the Convexity of Latent Social Network Inference
5:40 - 6:00pm	Spotlights Session 13
	A. Strehl, L. Li, J. Langford, S. Kakade Learning from Logged Implicit Exploration Data G. Isely, C. Hillar, F. Sommer Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication D. Grangier, I. Melvin Feature Set Embedding for Incomplete Data D. Sontag, O. Meshi, T. Jaakkola, A. Globerson More data means less inference: A pseudo-max approach to structured learning
7:00 - 11:59pm	Poster Session
	S. Mosci, S. Villa, A. Verri, L. Rosasco W1 A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups C. Micchelli, J. Morales, M. Pontil W2 A Family of Penalty Functions for Structured Sparsity A. Gelfand, Y. Chen, L. van der Maaten, M. Welling W3 On Herding and the Perceptron Cycling Theorem R. Salakhutdinov, N. Srebro W4 Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm Y. Zhang, J. Schneider W5 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty A. Agarwal, H. Daume III, S. Gerber W6 Learning Multiple Tasks using Manifold Regularization S. Bengio, J. Weston, D. Grangier W7 Label Embedding Trees for Large Multi-Class Tasks K. Crammer, D. Lee W8 Learning via Gaussian Herding N. Fisher, A. Banerjee W9 A Novel Kernel for Learning a Neuron Model from Spike Train Data D. Sontag, O. Meshi, T. Jaakkola, A. Globerson W10 More data means less inference: A pseudo-max approach to structured learning J. Sharpnack, A. Singh W11 Identifying graph-structured activation patterns in networks A. Shojaie, G. Michailidis W12 Penalized Principal Component Regression on Graphs for Analysis of Subnetworks D. Grangier, I. Melvin W13 Feature Set Embedding for Incomplete Data H. Larochelle, G. Hinton W14 Learning to combine foveal glimpses with a third-order Boltzmann machine S. Levine, Z. Popovic, V. Koltun W15 Feature Construction for Inverse Reinforcement Learning H. Xu, S. Mannor W16 Distributionally Robust Markov Decision Processes U. Syed, R. Schapire W17 A Reduction from Apprenticeship Learning to Classification M. Araya, O. Buffet, V. Thomas, F. Charpillet W18 A POMDP Extension with Belief-dependent Rewards J. Tang, P. Abbeel W19 On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient A. Strehl, J. Langford, L. Li, S. Kakade W20 Learning from Logged Implicit Exploration Data E. Todorov W21 Policy gradients in linearly-solvable MDPs J. Duchi, A. Agarwal, M. Wainwright W22 Distributed Dual Averaging In Networks U. Shalit, D. Weinshall, G. Chechik W23 Online Learning in The Manifold of Low-Rank Matrices J. Liu, J. Ye W24 Moreau-Yosida Regularization for Grouped Tree Structure Learning Y. Wu, S. Lin, H. Chen W25 A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration F. Triefenbach, A. Jalalvand, B. Schrauwen, J. Martens W26 Phoneme Recognition with Large Hierarchical Reservoirs H. Liu, X. Chen W27 Multivariate Dyadic Regression Trees for Sparse Learning Problems T. Kim, G. Shakhnarovich, R. Urtasun W28 Sparse Coding for Learning Interpretable Spatio-Temporal Primitives F. Nie, H. Huang, X. Cai, C. Ding W29 Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization A. Miyamae, Y. Nagata, I. Ono, S. Kobayashi W30 Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks J. Johns, C. Painter-Wakefield, R. Parr W31 Linear Complementarity for Regularized Policy Evaluation and Improvement X. Zhang, A. Saha, S. Vishwanathan W32 Lower Bounds on Rate of Convergence of Cutting Plane Methods J. Zhu, L. Li, F. Li, E. Xing W32 Large Margin Learning of Upstream Scene Understanding Models P. Welinder, S. Branson, S. Belongie, P. Perona W33 The Multidimensional Wisdom of Crowds D. Lee, A. Gupta, M. Hebert, T. Kanade W35 Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces S. Harmeling, M. Hirsch, B. Schölkopf W36 Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake w. brendel, S. Todorovic W37 Segmentation as Maximum-Weight Independent Set M. Ranzato, V. Mnih, G. Hinton W38 Generating more realistic images using gated MRF's Y. Wang, G. Mori W39 A Discriminative Latent Model of Image Region and Object Tag Correspondence L. Karlinsky, M. Dinerstein, S. Ullman W40 Using body-anchored priors for identifying actions in single images M. Blaschko, A. Vedaldi, A. Zisserman W41 Simultaneous Object Detection and Ranking with Weak Supervision S. Yu W42 Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike Z. Syed, J. Guttag W43 Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch Y. Maron, M. Lamar, E. Bienenstock W44 Sphere Embedding: An Application to Part-of-Speech Induction A. Joulin, F. Bach, J. Ponce W45 Efficient Optimization for Discriminative Latent Class Models H. Narayanan, S. Mitter W46 Sample Complexity of Testing the Manifold Hypothesis P. Viappiani, C. Boutilier W47 Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets G. Bellala, S. Bhavnani, C. Scott W48 Extensions of Generalized Binary Search to Group Identification and Exponential Costs S. Huang, R. Jin, Z. Zhou W49 Active Learning by Querying Informative and Representative Examples Y. Guo W50 Active Instance Sampling via Matrix Partition H. Liu, L. Latecki, s. yan W51 Robust Clustering as Ensembles of Affinity Relations P. Awasthi, R. Bosagh Zadeh W52 Supervised Clustering K. Chaudhuri, S. Dasgupta W53 Rates of convergence for the cluster tree A. Dhesi, P. Kar W54 Random Projection Trees Revisited Y. Zhang, D. Yeung W55 Worst-Case Linear Discriminant Analysis P. Jain, R. Meka, I. Dhillon W56 Guaranteed Rank Minimization via Singular Value Projection M. Hein, T. Bühler W57 An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA J. Petterson, A. Smola, T. Caetano, W. Buntine, S. Narayanamurthy W58 Word Features for Latent Dirichlet Allocation S. Seth, I. Park, A. Brockmeier, M. Semework, J. Choi, J. Francis, J. Principe W59 A novel family of non-parametric cumulative based divergences for point processes G. Varoquaux, A. Gramfort, J. Poline, B. Thirion W60 Brain covariance selection: better individual functional connectivity models using population prior K. Motwani, N. Adluru, C. Hinrichs, a. Alexander, V. Singh W61 Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures R. Cuingnet, M. Chupin, H. Benali, O. Colliot W62 Spatial and anatomical regularization of SVM for brain image analysis M. Mørup, K. Madsen, A. Dogonowski, h. Siebner, L. Hansen W63 Infinite Relational Modeling of Functional Connectivity in Resting State fMRI G. Langs, Y. Tie, L. Rigolo, A. Golby, P. Golland W64 Functional Geometry Alignment and Localization of Brain Areas K. Katahira, K. Okanoya, M. Okada W65 Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks G. Isely, C. Hillar, F. Sommer W66 Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication R. Kelly, M. Smith, K. Rob, T. Lee W67 Accounting for network effects in neuronal responses using L1 regularized point process models B. Gibson, X. Zhu, T. Rogers, C. Kalish, J. Harrison W68 Humans Learn Using Manifolds, Reluctantly A. Wohrer, R. Romo, C. Machens W69 Linear readout from a neural population with partial correlation data D. Ganguli, E. Simoncelli W70 Implicit encoding of prior probabilities in optimal neural populations S. Bohte, J. Rombouts W71 Fractionally Predictive Spiking Neurons V. Gogate, W. Webb, P. Domingos W72 Learning Efficient Markov Networks M. Khan, B. Marlin, G. Bouchard, K. Murphy W73 Variational bounds for mixed-data factor analysis J. Mooij, O. Stegle, D. Janzing, K. Zhang, B. Schölkopf W74 Probabilistic latent variable models for distinguishing between cause and effect H. Liu, X. Chen, J. Lafferty, L. Wasserman W75 Graph-Valued Regression J. Ayres Pereira, M. Ibrahimi, A. Montanari W76 Learning Networks of Stochastic Differential Equations G. Elidan W77 Copula Bayesian Networks N. Ding, S. Vishwanathan W78 t-logistic regression B. Frigyik, M. Gupta, Y. Chen W79 Shadow Dirichlet for Restricted Probability Modeling M. Hoffman, D. Blei, F. Bach W80 Online Learning for Latent Dirichlet Allocation M. Opper, A. Ruttor, G. Sanguinetti W81 Approximate inference in continuous time Gaussian-Jump processes S. Nakajima, M. Sugiyama, R. Tomioka W82 Global Analytic Solution for Variational Bayesian Matrix Factorization R. Adams, Z. Ghahramani, M. Jordan W83 Tree-Structured Stick Breaking for Hierarchical Data D. Lin, E. Grimson, J. Fisher W84 Construction of Dependent Dirichlet Processes based on Poisson Processes M. Alvarez, J. Peters, B. Schölkopf, N. Lawrence W85 Switched Latent Force Models for Movement Segmentation I. Murray, R. Adams W86 Slice sampling covariance hyperparameters of latent Gaussian models J. Huang, N. Jojic, C. Meek W87 Exact inference and learning for cumulative distribution functions on loopy graphs A. Chechetka, C. Guestrin W88 Evidence-Specific Structures for Rich Tractable CRFs S. Myers, J. Leskovec W89 On the Convexity of Latent Social Network Inference A. Kulesza, B. Taskar W90 Structured Determinantal Point Processes U. Dick, P. Haider, T. Vanck, M. Brückner, T. Scheffer W91 Throttling Poisson Processes K. Ishiguro, T. Iwata, N. Ueda, J. Tenenbaum W92 Dynamic Infinite Relational Model for Time-varying Relational Data Analysis T. Glasmachers W93 Universal Consistency of Multi-Class Support Vector Classification H. Narayanan, A. Rakhlin W94 Random Walk Approach to Regret Minimization G. Neu, A. György, C. Szepesvari, A. Antos W95 Online Markov Decision Processes under Bandit Feedback F. Orabona, K. Crammer W96 New Adaptive Algorithms for Online Classification A. Bernstein, S. Mannor, N. Shimkin W97 Online Classification with Specificity Constraints M. Bayati, J. Ayres Pereira, A. Montanari W98 The LASSO risk: asymptotic results and real world examples S. Sabato, N. Srebro, N. Tishby W99 Tight Sample Complexity of Large-Margin Learning A. Christmann, I. Steinwart W100 Universal Kernels on Non-Standard Input Spaces
7:30 - 11:59pm	Demonstrations
	A. Hornecker BCI Demonstration using a Dry-Electrode N. Quadrianto Globby: It's a Search Engine with a Sorting View F. Fleuret Platform to Share Feature Extraction Methods D. Wingate Stochastic Matlab S. Sonnenburg The SHOGUN Machine Learning Toolbox V. de Ladurantaye Visual Object Recognition with NN Convolutional & Spiking; Test on Traffic Signs
Thursday, December 9
7:30 - 9:00am	Breakfast
8:00 - 9:00am	Breakfast
8:00 - 11:00am	Internet Cafe
8:00 - 11:00am	Registration Desk
9:00 - 10:10am	Oral Session 17Session Chair:Rob Fergus
	Martin Banks Perceptual Bases for Rules of Thumb in Photography H. Larochelle, G. Hinton Learning to combine foveal glimpses with a third-order Boltzmann machine
10:10 - 10:40am	Break
10:40 - 11:50am	Oral Session 18Session Chair:David Blei
	J. Tenenbaum How to Grow a Mind: Statistics, Structure and Abstraction B. Gibson, X. Zhu, T. Rogers, C. Kalish, J. Harrison Humans Learn Using Manifolds, Reluctantly
2:00 - 5:00pm	The Sam Roweis SymposiumSession Chair:Maneesh Sahani
	Zoubin Ghahramani Unifying Views in Unsupervised Learning Lawrence Saul Manifold Learning Geoffrey Hinton A Probabilistic Approach to Data Visualization Yoram Singer Learning Structural Sparsity David Hogg Automating Astronomy

Workshops (December 10-11, 2010)

Thursday, December 9
4:00 - 8:00pm	Registration Desk
7:30 - 7:45pm	Terrence Sejnowski, Neil Lawrence Opening Remarks
7:30 - 9:00pm	Reception
Friday, December 10
6:30 - 8:00am	Breakfast
7:00 - 11:00am	Registration Desk
7:30am - 6:30pm	Craig Saunders, Jakob Verbeek, Svetlana Lazebnik Beyond classification: Machine Learning for next generation Computer Vision challenges
7:30am - 6:30pm	Ben Taskar, David Weiss, Benjamin Sapp, Slav Petrov Coarse-to-Fine Learning and Inference
7:30am - 6:30pm	Jennifer Wortman Vaughan, Hanna Wallach Computational Social Science and the Wisdom of Crowds
7:30am - 6:30pm	Miroslav Karny, Tatiana Guy, David Wolpert Decision Making with Multiple Imperfect Decision Makers
7:30am - 6:30pm	Honglak Lee, Marc'Aurelio Ranzato, Yoshua Bengio, Geoffrey Hinton, Yann LeCun, Andrew Ng Deep Learning and Unsupervised Feature Learning
7:30am - 6:30pm	Jesse Hoey, Pascal Poupart, Thomas Ploetz Machine Learning for Assistive Technologies
7:30am - 6:30pm	Gunnar Raetsch, Jean-Philippe Vert, Tomer Hertz, Yanjun Qi Machine Learning in Computational Biology
7:30am - 6:30pm	James Shanahan, Deepak Agarwal, Tao Qin, Tie-Yan Liu Machine Learning in Online Advertising
7:30am - 6:30pm	Louis-Philippe Morency, Daniel Gatica-Perez, Nigel Ward Modeling Human Communication Dynamics
7:30am - 6:30pm	Ryan Adams, Mark Girolami, Iain Murray Monte Carlo Methods for Bayesian Inference in Modern Day Applications
7:30am - 6:30pm	Suvrit Sra, Sebastian Nowozin, Stephen Wright Optimization for Machine Learning
7:30am - 6:30pm	Irina Rish, Alexandru Niculescu-Mizil, Guillermo Cecchi, Aurelie Lozano Practical Application of Sparse Modeling: Open Issues and New Directions
7:30am - 6:30pm	Pradeep Ravikumar, Constantine Caramanis, Sujay Sanghavi Robust Statistical Learning
7:30am - 6:30pm	Tamara Kolda, Vicente Malave, David Gleich, Johan Suykens, Marco Signoretto, Andreas Argyriou Tensors, Kernels, and Machine Learning
3:30 - 6:00pm	Registration Desk
Saturday, December 11
6:30 - 8:00am	Breakfast
7:00 - 11:00am	Registration Desk
7:30am - 6:30pm	Paul Munro Advances in Activity-Dependent Synaptic Plasticity
7:30am - 6:30pm	Barbara Hammer, Laurens van der Maaten, Fei Sha, Alexander Smola Challenges of Data Visualization
7:30am - 6:30pm	Pierre Baldi, Klaus-Robert Müller, Gisbert Schneider Charting Chemical Space: Challenges and Opportunities for AI and Machine Learning
7:30am - 6:30pm	Andreas Krause, Pradeep Ravikumar, Jeff Bilmes, Stefanie Jegelka Discrete Optimization in Machine Learning: Structures, Algorithms and Applications
7:30am - 6:30pm	Dan Lizotte, Michael Bowling, Susan Murphy, Joelle Pineau, Sandeep Vijan Learning and Planning from Batch Time Series Data
7:30am - 6:30pm	Alekh Agarwal, Lawrence Cayton, Ofer Dekel, John Duchi, John Langford Learning on Cores, Clusters, and Clouds
7:30am - 6:30pm	Arthur Gretton, Michael Mahoney, Mehryar Mohri, Ameet Talwalkar Low-rank Methods for Large-scale Machine Learning
7:30am - 6:30pm	Zenglin Xu, Irwin King, Shenghuo Zhu, Alan Qi, Rong Yan, John Yen Machine Learning for Social Computing
7:30am - 6:30pm	Stefan Harmeling, Michael Hirsch, Bill Freeman, Peyman Milanfar Machine Learning meets Computational Photography
7:30am - 6:30pm	Edoardo Airoldi, Anna Goldenberg, Jure Leskovec, Quaid Morris Networks Across Disciplines: Theory and Applications
7:30am - 6:30pm	Marius Kloft, Ulrich Rueckert, Cheng Soon Ong, Alain Rakotomamonjy, Soeren Sonnenburg, Francis Bach New Directions in Multiple Kernel Learning
7:30am - 6:30pm	Matthias Seeger, Suvrit Sra Numerical Mathematics Challenges in Machine Learning
7:30am - 6:30pm	Faisal Farooq, Glenn Fung, Romer Rosales, Shipeng Yu, Jude Shavlik, Balaji Krishnapuram, Raju Kucherlapati Predictive Models in Personalized Medicine
7:30am - 6:30pm	Russ Salakhutdinov, Ryan Adams, Josh Tenenbaum, Zoubin Ghahramani, Tom Griffiths Transfer Learning Via Rich Generative Models.
7:30 - 10:30pm	Workshops Banquet

The schedule was last modified on 2010-12-20 19:06 PST