NIPS 2008

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Time	Regency D	Regency E/F
Mon Dec 08, 2008
09:30 AM (Tutorials)	Prequential Analysis	Compressed Sensing
01:00 PM (Tutorials)	The Neurobiology of Decision Making	Agnostic Learning: Algorithms and Theory
03:30 PM (Tutorials)	The Smoothed Analysis of Algorithms	Statistical Models of Visual Images

Time	Hilton: Sutcliffe A	Hilton: Sutcliffe B	Hilton: Black Tusk	Westin: Emerald A	Hilton: Mt. Currie S	Westin: Glacier	Westin: Callaghan	Hilton: Diamond Head	Westin: Nordic	Hilton: Cheakamus	Hilton: Mt. Currie N	Westin: Alpine AB	Westin: Alpine CD	Westin: Alpine E
Fri Dec 12, 2008
07:30 AM (Workshops)	New Challanges in Theoretical Machine Learning: Data Dependent Concept Spaces	Structured Input - Structured Output	Machine learning meets human learning	Beyond Search: Computational Intelligence for the Web (day 1)	Machine Learning in Computational Biology	Principled Theoretical Frameworks for the Perception-Action Cycle	Algebraic and combinatorial methods in machine learning	Optimization for Machine Learning	Causality: objectives and assessment	Speech and Language: Learning-based Methods and Systems	Statistical Analysis and Modeling of Response Dependencies in Neural Populations (day 1)	Analyzing Graphs: Theory and Applications	Machine Learning Open Source Software	Cost Sensitive Learning

Time	Hilton: Sutcliffe A	Hilton: Sutcliffe B	Hilton: Black Tusk	Westin: Emerald A	Westin: Callaghan	Hilton: Diamond Head	Westin: Nordic	Hilton: Cheakamus	Hilton: Mt. Currie N	Westin: Alpine AB	Westin: Alpine CD	Westin: Alpine E
Sat Dec 13, 2008
07:30 AM (Workshops)	Parallel Implementations of Learning Algorithms: What have you done for me lately?	New Directions in Statistical Learning for Meaningful and Reproducible fMRI Analysis	Stochastic Models of Behaviour	Beyond Search: Computational Intelligence for the Web (day 2)	Model Uncertainty and Risk in Reinforcement Learning	Cortical Microcircuits and their Computational Functions	Kernel Learning: Automatic Selection of Optimal Kernels	Speech and Language: Unsupervised Latent-Variable Models	Statistical Analysis and Modeling of Response Dependencies in Neural Populations (day 2)	Approximate inference - how far have we come?	Probabilistic Programming: Universal Languages, Systems and Applications	Learning from Multiple Sources