The city of Haifa


For Participants

For authors


ICML 2010 - Schedule

Download the full program to your own calendar: HTML ICAL XML

Mon 09.00 (Tamar) Geometric Tools for Identifying Structure in Large Social and Information Networks
Michael W. Mahoney
Mon 09.00 (Rimon) Domain Adaptation
Hal Daume & John Blitzer
Mon 09.00 (Alon) Sparse Modeling: Theory, Algorithms and Applications
Irina Rish & Genady Grabarnik

Mon 13.00 (Alon) Learning through Exploration
Alina Beygelzimer and John Langford
Mon 13.00 (Tamar) Metric Learning
Brian Kulis
Mon 13.00 (Rimon) Privacy-preserving Data Mining
Stan Matwin

Mon 16.00 (Rimon) Sparse Modeling: Theory, Algorithms and Applications
Irina Rish & Genady Grabarnik
Mon 16.00 (Tamar) Domain Adaptation
Hal Daume & John Blitzer
Mon 16.00 (Alon) Stochastic Optimization for Machine Learning
Nathan Srebro and Ambuj Tewari

Tue 08.30 (Oren) ICML Opening
Tue 09.00 (Oren) Invited Talk: Tom Mitchell
Tue 10.30 (Alon) Topic Models and Matrix Factorization
Tue 10.30 (Tamar) Reinforcement Learning 1
Tue 10.30 (Rimon) Ensemble Methods
Tue 10.30 (Hadas) Statistical Relational Learning
Tue 10.30 (Arava) Large-Scale Learning and Optimization
Tue 13.30 (Alon) Matrix Factorization and Recommendation
Tue 13.30 (Tamar) Reinforcement Learning 2
Tue 13.30 (Rimon) Deep Learning 1
Tue 13.30 (Hadas) Multi-Task and Transfer Learning
Tue 13.30 (Oren) Ranking and Preference Learning
Tue 15.40 (Alon) Latent-Variable Models
Tue 15.40 (Tamar) Reinforcement Learning 3
Tue 15.40 (Rimon) Deep Learning 2
Tue 15.40 (Hadas) Structured Output Learning
Tue 15.40 (Oren) Dimensionality Reduction 1
Tue 17.30 (Oren) Best 10-Year Paper: Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
Erin L. Allwein, Robert E. Schapire, Yoram Singer
Tue 18.00
(Oren Foyer)
Poster Session 1

Wed 08.30 (Oren) Best Paper: Hilbert Space Embeddings of Hidden Markov Models
L. Song, B. Boots, S. Siddiqi, G. Gordon, A. Smola
Wed 09.00 (Oren) Invited Talk: Duncan Watts
Wed 10.30 (Alon) Graph Clustering
Wed 10.30 (Tamar) Reinforcement Learning 4
Wed 10.30 (Rimon) Risk estimation and Cost-sensitive Learning
Wed 10.30 (Hadas) Kernels
Wed 10.30 (Oren) Dimensionality Reduction 2
Wed 13.30 (Oren) Guest Lecture: Robert Aumann
Wed 14.30 (Oren) Best Application Paper:
Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process
K. Canini, M. Shashkov, T. Griffiths
Wed 15.40 (Alon) Invited Applications 1
Wed 15.40 (Tamar) Clustering 1
Wed 15.40 (Rimon) Causal Inference
Wed 15.40 (Hadas) Large Margin Methods
Wed 15.40 (Oren) Compact Representations
Wed 19.00 Banquet

Thu 08.30 (Oren) Best Student Paper: On the Consistency of Ranking Algorithms
J. Duchi, L. Mackey, M. Jordan
Thu 09.00 (Oren) Invited Talk: Nir Friedman
Thu 10.30 (Alon) Graphical Models
Thu 10.30 (Tamar) Clustering 2
Thu 10.30 (Rimon) Feature and Kernel Selection
Thu 10.30 (Hadas) Learning Theory
Thu 10.30 (Oren) Exploration and Feature Construction
Thu 13.30 (Alon) Invited Applications 2
Thu 13.30 (Tamar) Semi-Supervised Learning 1
Thu 13.30 (Rimon) Gaussian Processes
Thu 13.30 (Hadas) Online Learning
Thu 13.30 (Oren) Multi-Agent Learning
Thu 15.40 (Alon) Graphical Models and Bayesian Methods
Thu 15.40 (Tamar) Semi-Supervised Learning 2
Thu 15.40 (Rimon) Time-Series Analysis
Thu 15.40 (Hadas) Online and Active Learning
Thu 15.40 (Oren) Multi-Label and Multi-Instance Learning
Thu 17.30 (Oren) Business Meeting
Thu 18.30
(Oren Foyer)
Poster Session 2

Fri 08.30 (King Shlomo, Dan Carmel) Budgeted Learning
Dragos Margineantu, Russell Greiner, Tomas Singliar and Prem Melville

Fri 09.00 (Alon, Dan Panorama) Reinforcement Learning and Search in Very Large Spaces
Peter Auer, Samuel Kaski and Csaba Szepesvari
Fri 09.00 (Rimon, Dan Carmel) Social Analytics: Learning from Human Interactions
Elad Yom-Tov, Shie Mannor and Yossi Richter
Fri 09.00 (Erez, Dan Panorama) Machine Learning and Open Source Software
Soeren Sonnenburg, Mikio Braun, Cheng Soon Ong and Patrik Hoyer
Fri 09.00 (Dekel, Dan Carmel) Learning to Rank Challenge
Tie-Yan Liu, Olivier Chapelle and Yi Chang
Fri 09.00 (Oren, Dan Panorama) Topic Models; Structure, Applications, Evaluation, and Extensions
Michal Rosen-Zvi, Amit Gruber and Richard Zemel
Fri 09.00 (King David, Dan Carmel) Learning from Multi-Label Data
Min-Ling Zhang, Grigorios Tsoumakas and Zhi-Hua Zhou
Fri 09.00 (Brosh, Dan Panorama) Machine Learning and Games
Kurt Driessens, Olana Missura and Christian Thurau
Fri 09.00 (Tomer, Dan Panorama) Learning in Non-(geo)metric Spaces
Joachim Buhmann, Robert Duin, Mario Figueiredo, Edwin Hancock, Vittorio Murino and Marcello Pelillo