See also: an overview of all co-located meetings and ICML detailed schedule
ICML schedule at a glance
| Sunday July 6, 2008 | |||
| Breakfast in hotel | |||
| Sun | 8:00 am - | Registration | |
| Sun | 8:30 am - 8:45 am | S1 | Opening, S1 |
| Sun | 8:45 am - 9:45 am | S1 | Invited Talk #1: John Winn, Microsoft Research Cambridge: Probabilistic models for understanding images |
| Sun | 9:45 am - 10:15 am | Coffee Break | |
| Sun | 10:15 am - 11:55 am | S13 | Reinforcement Learning 1 - Domain Representation: Papers #571 #544 #682 #258 |
| Sun | 10:15 am - 11:55 am | S1 | Kernels: Papers #377 #277 #216 #643 |
| Sun | 10:15 am - 11:55 am | S5 | Clustering: Papers #628 #196 #236 #168 |
| Sun | 10:15 am - 11:55 am | S12 | Hidden Markov Models: Papers #182 #305 #413 #679 |
| Sun | 10:15 am - 11:55 am | SH | Graphs: Papers #379 #681 #565 #396 |
| 12:00 pm - 1:30 pm | Lunch | ||
| 1:30 pm - 3:10 pm | Sun 1:30 pm S13
Reinforcement Learning 2 - Value Representation: Papers
#341
#125
#581
#429
Sun 1:30 pm S1 Active Learning, Experimental design and Incomplete data: Papers #324 #437 #687 #272 Sun 1:30 pm S5 Distance learning and Efficient Use: Papers #215 #178 #400 #340 Sun 1:30 pm SH Mixture models, Dirichlet processes: Papers #460 #538 #554 #502 Sun 1:30 pm S12 Optimization: Papers #327 #461 #497 3260 | ||
| 3:10 pm - 3:40 pm | Coffee Break | ||
| 3:40 pm - 5:45 pm | Award Paper Joint Session | ||
| Sun 3:40 pm S1 Papers: #xxx #588 #627 #266 #452 | |||
| 6:00 pm - 8:30 pm | Poster Session I (with snacks) | ||
| Monday July 7, 2008 | |||
| Breakfast in hotel | |||
| 8:00 am - | Registration | ||
| 8:30 am - 9:30 am | Invited Talk #2: Luc De Raedt, Katholieke Universiteit Leuven: Logical and Relational Learning Revisited | ||
| 9:30 am - 10:00 am | Coffee Break | ||
| 10:00 am - 12:05pm | Mon 10:00 am S13
Reinforcement Learning 3: Papers
#259
#488
#335
#257
Mon 10:00 am S5 Kernel - Including Kernel Learning: Papers #158 #665 #531 #449 #641 Mon 10:00 am SH Semi-supervised Learning - Embeddings and Transduction: Papers #611 #382 #296 #254 #383 Mon 10:00 am S12 Ranking and Bayes Optimal Classification: Papers #489 #343 #392 #448 #455 Mon 10:00 am S1 Structured output, ILP and Sparsity: Papers #402 #279 #530 #237 #503 | ||
| 12:05 pm - 1:30 pm | Lunch | ||
| 1:30 pm - 3:35 pm | Mon 1:30 pm S13
Reinforcement Learning 4 - Active Learning: Papers
#290
#487
#490
#479
#519
Mon 1:30 pm S1 Gaussian Processes: Papers #151 #241 #599 #371 #399 Mon 1:30 pm SH Semi-supervised clustering and classification: Papers #337 #432 #172 #145 #528 Mon 1:30 pm S5 Sequence Data: Papers #278 #318 #440 #180 #160 Mon 1:30 pm S12 Feature selection and sparsity: Papers #630 #574 #390 #113 #323 | ||
| 3:35 pm - 4:05 pm | Coffee Break | ||
| 4:05 pm - 5:05 pm | Invited talk #3: Michael Collins, MIT: Structured Prediction Problems in Natural Language Processing | ||
| 5:05 pm - 6:30 pm | Break, prep to leave for boats | ||
| 6:30 pm - 10:30 pm | Conference Banquet | ||
| Tuesday, July 8, 2008 | |||
| Breakfast in hotel | |||
| 8:00 am - | Registration | ||
| 8:30 am - 10:10 am | Tue 8:30 am S13
Reinforcement Learning 5: Papers
#452
#580
#645
#111
Tue 8:30 am S5 Boosting and Expert Advice: Papers #676 #331 #362 #242 Tue 8:30 am S1 Discriminative vs Generative, and Energy-Based Learning: Papers #415 #601 #573 #638 Tue 8:30 am SH Ranking and IR: Papers #167 #179 #470 #264 Tue 8:30 am S12 Compressed Sensing and Projections: Papers #121 #209 #459 #361 | ||
| 10:10 am - 10:40 am | Coffee Break | ||
| 10:40 am - 12:20 pm | Tue 10:40 am S13
Reinforcement Learning 6: Papers
#458
#564
#197
#317
Tue 10:40 am SH Online learning: Papers #367 #322 #355 #511 Tue 10:40 am S5 Embeddings: Papers #163 #484 #551 #600 Tue 10:40 am S1 Topic models: Papers #562 #419 #667 #129 Tue 10:40 am S12 Classification with Sampling, Costs: Papers #523 #614 #632 #150 | ||
| 12:20 pm - 2:00 pm | Lunch | ||
| 2:00 pm - 4:05 pm | Tue 2:00 pm S13
Transfer Learning and Games: Papers
#412
#520
#229
#542
#655
Tue 2:00 pm SH Kernels - Including scalability: Papers #166 #411 #491 #476 #513 Tue 2:00 pm S12 Embeddings: Papers #270 #668 #312 #582 #592 Tue 2:00 pm S1 NLP: Papers #304 #391 #398 #311 #673 Tue 2:00 pm S5 Multiple Instance Learning, Missing Features, Categorical Features: Papers #130 #552 #587 #202 #536 | ||
| 4:05 pm - 4:35 pm | Coffee Break | ||
| 4:35 pm - 5:35 pm | Invited Talk #4: Andrew Ng, Stanford University: STAIR: The STanford Artificial Intelligence Robot project | ||
| 5:40 pm - 6:30 pm | Business Meeting | ||
| 6:00 pm - 8:30 pm | Poster Session II (with snacks) | ||