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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
7:00 – 11:59pm Poster Session
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
10:10 – 10:40am Break
10:40am – 12:00pm Oral Session 2: Images and CodesSession Chair:Bill Triggs
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
3:20 – 3:40pm Spotlights
3:40 – 4:10pm Break
4:10 – 5:10pm Oral Session 4: Cognitive Science and EEG AnalysisSession Chair:Charles Kemp
5:10 – 5:30pm Spotlights
5:30 – 7:30pm Dinner Break
7:30 – 11:59pm Poster Session
7:30 – 11:59pm Demonstrations
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
10:10 – 10:40am Break
10:40am – 12:00pm Oral Session 6: Theory, Optimization and Games Session Chair:Ben Taskar
12:00 – 2:00pm Lunch Break
2:00 – 3:20pm Oral session 7: Vision and InferenceSession Chair:Antonio Torralba
3:20 – 3:40pm Spotlights
3:40 – 4:10pm Break
4:10 – 5:10pm Oral session 8: Probabilistic Models and KernelsSession Chair:Jon McAuliffe
5:10 – 5:30pm Spotlights
5:30 – 7:30pm Dinner Break
7:30 – 11:59pm Poster Session
7:30 – 11:59pm Demonstrations
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
9:50 – 10:30am Break
10:30 – 11:50am Oral session 10: Neural Modeling and ImagingSession Chair:Arthur Gretton
11:50am – 1:30pm Lunch Break
1:30 – 4:30pm Mini Symposia
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 Edo M Airoldi, Jure Leskovec, Jon Kleinberg, Josh Tenenbaum
Analyzing Networks and Learning With Graphs
7:30am – 6:30pm David Blei, Jordan L 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, Alex 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, Mate 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 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 W 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, Thomas 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, Nicolò 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