| Friday, December 10 |
|---|
| 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 |
Jenn Wortman Vaughan, Hanna Wallach
Computational Social Science and the Wisdom of Crowds |
| 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
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 |
| 7:30am - 6:30pm |
Miroslav Karny, Tatiana Guy, David Wolpert
Decision Making with Multiple Imperfect Decision Makers |
| Saturday, December 11 |
|---|
| 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 |
Daniel Lizotte, Michael Bowling, Susan Murphy, Joelle Pineau, Sandeep Vijan
Learning and Planning from Batch Time Series Data |
| 7:30am - 6:30pm |
John Duchi, Ofer Dekel, John Langford, Alekh Agarwal
Learning on Cores, Clusters, and Clouds |
| 7:30am - 6:30pm |
Michael Mahoney, Mehryar Mohri, Ameet Talwalkar
Low-rank Methods for Large-scale Machine Learning |
| 7:30am - 6:30pm |
Zenglin Xu, Irwin King, Shenghuo Zhu, Yuan (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
Networks across disciplines in 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, Inderjit Dhillon
Numerical Mathematics Challenges in Machine Learning |
| 7:30am - 6:30pm |
Faisal Farooq, Glenn Fung, Romer Rosales, Shipeng Yu, Jude Shavlik
Predictive Models in Personalized Medicine |
| 7:30am - 6:30pm |
Ruslan Salakhutdinov, Ryan Adams, Josh Tenenbaum, Zoubin Ghahramani, Tom Griffiths
Transfer Learning by Learning Rich Generative Models. |
