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ICML 2010 - Program
Jump to Detailed Version
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| Mon 09.00 | Geometric Tools for Identifying Structure in Large Social and Information Networks | Tamar |
| Domain Adaptation | Rimon | |
| Sparse Modeling: Theory, Algorithms and Applications | Alon | |
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| Mon 13.00 | Learning through Exploration | Alon | Metric Learning | Tamar |
| Privacy-preserving Data Mining | Rimon | |
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| Mon 16.00 | Sparse Modeling: Theory, Algorithms and Applications | Rimon |
| Domain Adaptation | Tamar | |
| Stochastic Optimization for Machine Learning | Alon | |
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| Tue 08.30 | ICML Opening | Oren |
| Tue 09.00 | Invited Talk: Tom Mitchell | Oren |
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| Tue 10.30 | Topic Models and Matrix Factorization | Alon |
| Papers: #45,#420,#384,#553 | ||
| Reinforcement Learning 1 | Tamar | |
| Papers: #336,#598,#187,#654 | ||
| Ensemble Methods | Rimon | |
| Papers: #263,#330,#99,#23 | ||
| Statistical Relational Learning | Hadas | |
| Papers: #77,#544,#502,#537 | ||
| Large-Scale Learning and Optimization | Arava | |
| Papers: #438,#562,#242,#311 | ||
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| Tue 13.30 | Matrix Factorization and Recommendation | Alon |
| Papers: #518,#523,#196,#505 | ||
| Reinforcement Learning 2 | Tamar | |
| Papers: #588,#593,#295,#269 | ||
| Deep Learning 1 | Rimon | |
| Papers: #100,#370,#451,#458 | ||
| Multi-Task and Transfer Learning | Hadas | |
| Papers: #620,#352,#219 | ||
| Ranking and Preference Learning | Oren | |
| Papers: #331,#353,#504,#605 | ||
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| Tue 15.40 | Latent-Variable Models | Alon |
| Papers: #397,#549,#371,#551 | ||
| Reinforcement Learning 3 | Tamar | |
| Papers: #475,#627,#464,#442 | ||
| Deep Learning 2 | Rimon | |
| Papers: #115,#149,#432,#441 | ||
| Structured Output Learning | Hadas | |
| Papers: #522,#586,#587 | ||
| Dimensionality Reduction 1 | Oren | |
| Papers: #195,#359,#556,#197 | ||
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| Tue 17.30 | Best 10-Year Paper | Oren | Tue 18.00 | Poster Session 1 | Oren Foyer |
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| Wed 08.30 | Best Paper: #495 | Oren |
| Wed 09.00 | Invited Talk: Duncan Watts | Oren |
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| Wed 10.30 | Graph Clustering | Alon |
| Papers: #119,#233,#387,#132 | ||
| Reinforcement Learning 4 | Tamar | |
| Papers: #303,#652,#571,#52 | ||
| Risk estimation and Cost-sensitive Learning | Rimon | |
| Papers: #376,#207,#285,#310 | ||
| Kernels | Hadas | |
| Papers: #125,#347,#520,#179 | ||
| Dimensionality Reduction 2 | Oren | |
| Papers: #374,#481,#123,#333 | ||
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| Wed 13.30 | Guest Lecture: Robert Aumann |
Oren |
| Wed 14.30 | Best Application Paper: #180 | Oren |
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| Wed 15.40 | Invited Applications 1 | Alon |
| Papers: #901,#902,#903 | ||
| Clustering 1 | Tamar | |
| Papers: #248,#279,#26,#168 | ||
| Causal Inference | Rimon | |
| Papers: #235,#78,#576,#28 | ||
| Large Margin Methods | Hadas | |
| Papers: #176,#569,#280,#268 | ||
| Compact Representations | Oren | |
| Papers: #449,#366,#416,#178 | ||
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| Wed 19.00 | Banquet | |
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| Thu 08.30 | Best Student Paper: #421 | Oren |
| Thu 09.00 | Invited Talk: Nir Friedman | Oren |
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| Thu 10.30 | Graphical Models | Alon |
| Papers: #286,#378,#202,#628 | ||
| Clustering 2 | Tamar | |
| Papers: #342,#582,#642,#521 | ||
| Feature and Kernel Selection | Rimon | |
| Papers: #540,#238,#247,#227 | ||
| Learning Theory | Hadas | |
| Papers: #319,#601,#554 | ||
| Exploration and Feature Construction | Oren | |
| Papers: #410,#546,#638,#454 | ||
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| Thu 13.30 | Invited Applications 2 | Alon |
| Papers: #904,#905,#906,#907 | ||
| Semi-Supervised Learning 1 | Tamar | |
| Papers: #16,#137,#643,#107 | ||
| Gaussian Processes | Rimon | |
| Papers: #636,#297,#412,#422 | ||
| Online Learning | Hadas | |
| Papers: #259,#429,#473,#298 | ||
| Multi-Agent Learning | Oren | |
| Papers: #76,#191,#284,#453 | ||
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| Thu 15.40 | Graphical Models and Bayesian Methods | Alon |
| Papers: #246,#592,#35,#568 | ||
| Semi-Supervised Learning 2 | Tamar | |
| Papers: #468,#275,#117,#223 | ||
| Time-Series Analysis | Rimon | |
| Papers: #493,#175,#170,#532 | ||
| Online and Active Learning | Hadas | |
| Papers: #406,#436,#446,#433 | ||
| Multi-Label and Multi-Instance Learning | Oren | |
| Papers: #87,#344,#589,#596 | ||
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| Thu 17.30 | Business Meeting | Oren | Thu 18.30 | Poster Session 2 | Oren Foyer |
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| Fri 08.30 | Budgeted Learning | King Shlomo, Dan Carmel |
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| Fri 09.00 | Reinforcement Learning and Search in Very Large Spaces | Alon, Dan Panorama |
| Social Analytics: Learning from Human Interactions | Rimon, Dan Carmel | |
| Machine Learning and Open Source Software | Erez, Dan Panorama | |
| Learning to Rank Challenge | Dekel, Dan Carmel | |
| Topic Models; Structure, Applications, Evaluation, and Extensions | Oren, Dan Panorama | |
| Learning from Multi-Label Data | King David, Dan Carmel | |
| Machine Learning and Games | Brosh, Dan Panorama | |
| Learning in Non-(geo)metric Spaces | Tomer, Dan Panorama |