NIPS 2010

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Time	NIPS Registration Desk, 3rd Floor Hyatt
Sun Dec 05, 2010
04:00 PM (Placeholders)	Registration Desk

Time	Regency D	Regency E/F	Regency Ballroom	Oxford Room	Registration Desk, 3rd Floor Hyatt
Mon Dec 06, 2010
08:00 AM (Placeholders)				Internet Cafe	Registration Desk
09:30 AM (Tutorials)		High-dimensional Statistics: Prediction, Association and Causal Inference
01:00 PM (Tutorials)	Reinforcement Learning in Humans and Other Animals	Optimization Algorithms in Machine Learning
03:30 PM (Tutorials)	Vision-Based Control, Control-Based Vision, and the Information Knot That Ties Them	Latent Factor Models for Relational Arrays and Network Data
06:15 PM (Talks)			Opening Remarks and Awards
06:30 PM (Spotlights)			Spotlights Session 1 Learning from Candidate Labeling Sets
06:35 PM (Spotlights)			Why are some word orders more common than others? A uniform information density account
06:40 PM (Spotlights)			Layered image motion with explicit occlusions, temporal consistency, and depth ordering
06:45 PM (Spotlights)			b-Bit Minwise Hashing for Estimating Three-Way Similarities
06:50 PM (Spotlights)			Getting lost in space: Large sample analysis of the resistance distance

Time	Regency Ballroom	Georgia A	Perspectives Level, 34th Floor Hyatt	Oxford Room	Regency A, Conference Level	Registration Desk, 3rd Floor Hyatt
Tue Dec 07, 2010
07:30 AM (Placeholders)			Breakfast
08:00 AM (Placeholders)				Internet Cafe	Breakfast	Registration Desk
08:30 AM (Invited Talks)	Oral Session 1 How Does the Brain Compute and Compare Values at the Time of Decision-Making?
09:20 AM (Orals)	Over-complete representations on recurrent neural networks can support persistent percepts
09:40 AM (Spotlights)	Spotlights Session 2 Improving Human Judgments by Decontaminating Sequential Dependencies
09:45 AM (Spotlights)	Learning to localise sounds with spiking neural networks
09:50 AM (Spotlights)	SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system
09:55 AM (Spotlights)	Attractor Dynamics with Synaptic Depression
10:00 AM (Orals)	Oral Session 2 A rational decision making framework for inhibitory control
10:50 AM (Orals)	Oral Session 3 A Theory of Multiclass Boosting
11:10 AM (Spotlights)	Spotlights Session 3 Copula Processes
11:15 AM (Spotlights)	A biologically plausible network for the computation of orientation dominance
11:20 AM (Spotlights)	Learning Convolutional Feature Hierarchies for Visual Recognition
11:25 AM (Spotlights)	LSTD with Random Projections
11:30 AM (Orals)	Oral Session 4 Online Learning: Random Averages, Combinatorial Parameters, and Learnability
11:50 AM (Spotlights)	Spotlights Session 4 Kernel Descriptors for Visual Recognition
11:55 AM (Spotlights)	Minimum Average Cost Clustering
12:00 PM (Spotlights)	Identifying Dendritic Processing
12:05 PM (Spotlights)	Probabilistic Inference and Differential Privacy
02:00 PM (Invited Talks)	Oral Session 5 Machine Learning with Human Intelligence: Principled Corner Cutting (PC2)
02:50 PM (Orals)	Fast global convergence rates of gradient methods for high-dimensional statistical recovery
03:10 PM (Spotlights)	Spotlights Session 5 Trading off Mistakes and Don't-Know Predictions
03:15 PM (Spotlights)	Exact learning curves for Gaussian process regression on large random graphs
03:20 PM (Spotlights)	Synergies in learning words and their referents
03:25 PM (Spotlights)	Learning concept graphs from text with stick-breaking priors
03:30 PM (Orals)	Oral Session 6 Structured sparsity-inducing norms through submodular functions
04:20 PM (Orals)	Oral Session 7 Semi-Supervised Learning with Adversarially Missing Label Information
04:40 PM (Orals)	MAP estimation in Binary MRFs via Bipartite Multi-cuts
05:00 PM (Spotlights)	Spotlights Session 6 Efficient Minimization of Decomposable Submodular Functions
05:05 PM (Spotlights)	Worst-case bounds on the quality of max-product fixed-points
05:10 PM (Spotlights)	Learning To Count Objects in Images
05:15 PM (Spotlights)	Learning invariant features using the Transformed Indian Buffet Process
05:20 PM (Orals)	Oral Session 8 A Dirty Model for Multi-task Learning
05:40 PM (Spotlights)	Spotlights Session 7 Multiple Kernel Learning and the SMO Algorithm
05:45 PM (Spotlights)	Variational Inference over Combinatorial Spaces
05:50 PM (Spotlights)	Inductive Regularized Learning of Kernel Functions
05:55 PM (Spotlights)	Probabilistic Deterministic Infinite Automata
07:30 PM (Demonstrations)		Demonstrations

Time	Regency A	Regency Ballroom	Georgia A	Perspectives Level, 34th Floor Hyatt	Oxford Room	Conference Level
Wed Dec 08, 2010
07:30 AM (Placeholders)				Breakfast
08:00 AM (Placeholders)	Breakfast				Internet Cafe	Registration Desk
08:30 AM (Invited Talks)		Oral Session 9 The Interplay of Machine Learning and Mechanism Design
09:20 AM (Orals)		Linear Complementarity for Regularized Policy Evaluation and Improvement
09:40 AM (Spotlights)		Spotlights Session 8 Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets
09:45 AM (Spotlights)		Online Classification with Specificity Constraints
09:50 AM (Spotlights)		Exact inference and learning for cumulative distribution functions on loopy graphs
09:55 AM (Spotlights)		Global Analytic Solution for Variational Bayesian Matrix Factorization
10:00 AM (Orals)		Oral Session 10 The Multidimensional Wisdom of Crowds
10:50 AM (Orals)		Oral Session 11 Construction of Dependent Dirichlet Processes based on Poisson Processes
11:10 AM (Spotlights)		Spotlights Session 9 Throttling Poisson Processes
11:15 AM (Spotlights)		Graph-Valued Regression
11:20 AM (Spotlights)		Switched Latent Force Models for Movement Segmentation
11:25 AM (Spotlights)		Online Markov Decision Processes under Bandit Feedback
11:30 AM (Orals)		Oral Session 12 Slice sampling covariance hyperparameters of latent Gaussian models
11:50 AM (Spotlights)		Spotlights Session 10 Distributed Dual Averaging In Networks
11:55 AM (Spotlights)		A Family of Penalty Functions for Structured Sparsity
12:00 PM (Spotlights)		Guaranteed Rank Minimization via Singular Value Projection
12:05 PM (Spotlights)		Online Learning for Latent Dirichlet Allocation
02:00 PM (Invited Talks)		Oral Session 13 Statistical Inference of Protein Structure and Function
02:50 PM (Orals)		Tree-Structured Stick Breaking for Hierarchical Data
03:10 PM (Spotlights)		Spotlights Session 11 Structured Determinantal Point Processes
03:15 PM (Spotlights)		Supervised Clustering
03:20 PM (Spotlights)		Online Learning in The Manifold of Low-Rank Matrices
03:25 PM (Spotlights)		Sample Complexity of Testing the Manifold Hypothesis
03:30 PM (Orals)		Oral Session 14 Identifying graph-structured activation patterns in networks
04:20 PM (Orals)		Oral Session 15 Phoneme Recognition with Large Hierarchical Reservoirs
04:40 PM (Orals)		Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
05:00 PM (Spotlights)		Spotlights Session 12 Functional Geometry Alignment and Localization of Brain Areas
05:05 PM (Spotlights)		Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
05:10 PM (Spotlights)		On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient
05:15 PM (Spotlights)		Shadow Dirichlet for Restricted Probability Modeling
05:20 PM (Orals)		Oral Session 16 On the Convexity of Latent Social Network Inference
05:40 PM (Spotlights)		Spotlights Session 13 Learning from Logged Implicit Exploration Data
05:45 PM (Spotlights)		Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication
05:50 PM (Spotlights)		Feature Set Embedding for Incomplete Data
05:55 PM (Spotlights)		More data means less inference: A pseudo-max approach to structured learning
07:30 PM (Demonstrations)			Demonstrations

Time	Regency A	Regency Ballroom	Perspectives Level, 34th Floor Hyatt	Oxford Room	Registration Desk, 3rd Floor Hyatt	Registration Desk, Westin Lobby, Whistler	Whistler Westin Emerald Ballroom
Thu Dec 09, 2010
07:30 AM (Placeholders)			Breakfast
08:00 AM (Placeholders)	Breakfast			Internet Cafe	Registration Desk
09:00 AM (Invited Talks)		Oral Session 17 Perceptual Bases for Rules of Thumb in Photography
09:50 AM (Orals)		Learning to combine foveal glimpses with a third-order Boltzmann machine
10:40 AM (Invited Talks)		Oral Session 18 How to Grow a Mind: Statistics, Structure and Abstraction
11:30 AM (Orals)		Humans Learn Using Manifolds, Reluctantly
04:00 PM (Placeholders)						Registration Desk
07:30 PM (Placeholders)							Reception

Time	Hilton: Sutcliffe A	Hilton: Sutcliffe B	Hilton: Black Tusk	Westin: Emerald A	Westin: Glacier	Westin: Callaghan	Hilton: Diamond Head	Westin: Nordic	Westin: Alpine DE	Westin: Alpine BC	Westin: Alpine A	Westin Lobby	Whistler Westin Lobby	Hilton: Mt Currie South	Hilton: Mt Currie North	Hilton: Cheakmus
Fri Dec 10, 2010
06:30 AM (Placeholders)												Breakfast
07:00 AM (Placeholders)													Registration Desk
07:30 AM (Workshops)	Practical Application of Sparse Modeling: Open Issues and New Directions	Machine Learning in Computational Biology	Decision Making with Multiple Imperfect Decision Makers	Optimization for Machine Learning	Machine Learning for Assistive Technologies	Computational Social Science and the Wisdom of Crowds	Machine Learning in Online Advertising	Tensors, Kernels, and Machine Learning	Coarse-to-Fine Learning and Inference	Beyond classification: Machine Learning for next generation Computer Vision challenges	Modeling Human Communication Dynamics			Robust Statistical Learning	Monte Carlo Methods for Bayesian Inference in Modern Day Applications	Deep Learning and Unsupervised Feature Learning
03:30 PM (Placeholders)													Registration Desk

Time	Hilton: Sutcliffe A	Hilton: Sutcliffe B	Hilton: Black Tusk	Westin: Emerald A	Westin: Glacier	Westin: Callaghan	Hilton: Diamond Head	Westin: Nordic	Westin: Alpine DE	Westin: Alpine BC	Westin: Alpine A	Westin Lobby	Whistler Westin Lobby	Westin Emerald Ballroom	Hilton: Mt Currie South	Hilton: Mt Currie North	Hilton: Cheakmus
Sat Dec 11, 2010
06:30 AM (Placeholders)												Breakfast
07:00 AM (Placeholders)													Registration Desk
07:30 AM (Workshops)	Learning and Planning from Batch Time Series Data	Predictive Models in Personalized Medicine	Machine Learning meets Computational Photography	Transfer Learning Via Rich Generative Models.	Charting Chemical Space: Challenges and Opportunities for AI and Machine Learning	Advances in Activity-Dependent Synaptic Plasticity	Numerical Mathematics Challenges in Machine Learning	Networks Across Disciplines: Theory and Applications	Challenges of Data Visualization	Low-rank Methods for Large-scale Machine Learning	Machine Learning for Social Computing				Learning on Cores, Clusters, and Clouds	New Directions in Multiple Kernel Learning	Discrete Optimization in Machine Learning: Structures, Algorithms and Applications
07:30 PM (Placeholders)														Workshops Banquet

Sun Dec 05, 2010

Mon Dec 06, 2010

Tue Dec 07, 2010

Wed Dec 08, 2010

Thu Dec 09, 2010

Fri Dec 10, 2010

Sat Dec 11, 2010