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Timezone: America/Vancouver »

Indicates the beginning of a session

 Mon Dec 03, 2007

Time Regency A, Level 3
07:30 AM (Breaks)
Breakfast

 Tue Dec 04, 2007

Time 34th floor
07:30 AM (Breaks)
Breakfast

 Wed Dec 05, 2007

Time 34th floor
07:30 AM (Breaks)
Breakfast

 Thu Dec 06, 2007

Time Hyatt Regency, Vancouver 34th floor Emerald Ballroom Westin, Whistler
07:30 AM (Breaks)
Breakfast
08:00 AM (Breaks)
Registration (Hyatt)
05:00 PM (Breaks)
Registration (Westin)
06:30 PM (Breaks)
Welcoming Reception

 Fri Dec 07, 2007

Time Hilton: Sutcliffe A Hilton: Sutcliffe B Westin: Alpine (D-E) Westin: Alpine A-C Hilton: Black Tusk Westin: Nordic Westin: Emerald A Hilton: Mt. Currie S Westin: Glacier Hilton: Mt. Currie N. Hilton: Diamond Head Westin: Callaghan Westin Hotel, Emerald C Ballroom Emerald Room
06:30 AM (Breaks)
Breakfast
07:30 AM (Workshops)
Principles of Learning Problem Design
Machine Learning for Systems Problems (Part 1)
Music, Brain and Cognition. Part 1: Learning the Structure of Music and Its Effects On the Brain
Beyond Simple Cells: Probabilistic Models for Visual Cortical Processing
Robotics Challenges for Machine Learning
Machine Learning in Computational Biology (Part 1)
Large Scale Brain Dynamics (Part 1)
Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1)
Topology Learning: New Challenges At the Crossing of Machine Learning,
Machine Learning for Web Search
Approximate Bayesian Inference in Continuous/Hybrid Models
09:00 AM (Workshops)
Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 1)
07:00 PM (Workshops)
IBM Student Reception

 Sat Dec 08, 2007

Time Hilton: Sutcliffe A Hilton: Sutcliffe B Westin: Emerald A Hilton: Mt. Currie S Westin: Glacier Westin: Callaghan Westin: Alpine A-C Hilton: Diamond Head Westin: Nordic Westin: Alpine D-E Hilton: Cheakamus Hilton: Black Tusk Hilton: Mt. Currie N Emerald Room Emerald Ballroom
06:30 AM (Breaks)
Breakfast
07:30 AM (Workshops)
Machine Learning for Systems Problems (Part 2)
Large Scale Brain Dynamics (Part 2)
Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 2)
The Grammar of Vision: Probabilistic Grammar-Based Models for Visual Scene Understanding and Object Categorization
Representations and Inference on Probability Distributions
Machine Learning in Computational Biology (Part 2)
Music, Brain and Cognition. Part 2: Models of Sound and Cognition
Statistical Network Models
08:30 AM (Workshops)
Mechanisms of Visual Attention
09:00 AM (Workshops)
Machine Learning in Adversarial Environments for Computer Security
Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 2)
The Urban Challenge – Perspectives of Autonomous Driving
Machine Learning and Games (MALAGA): Open Directions in Applying Machine Learning to Games
07:30 PM (Breaks)
Banquet and Wrap up Meeting