| Monday, April 13 | ||
| 16:00 | Registration | |
| 18:00 | Dinner | |
| 19:30 | Oral Session 1 | |
| 19:30 | Evaluation Methods for Topic Models Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David Mimno |
[DjVu|PDF] |
| 19:50 | The graphlet spectrum Risi Kondor and Nino Shervashidze and Karsten Borgwardt |
[DjVu|PDF] |
| 20:10 | Break | |
| 20:30 | Terence Sanger Failure of Motor Learning and How to Succeed Anyway |
[DjVu|PDF] |
| 21:10 | Adjourn | |
| Tuesday, April 14 | ||
| 08:00 | Breakfast | |
| 09:00 | Oral Session 2 | |
| 09:00 | A Graphical Model Viewpoint on Queueing Networks Charles Sutton and Michael I. Jordan |
[DjVu|PDF] |
| 09:20 | Consistent Robust Logarithmic Time Prediction John Langford (but on joint work with many other coauthors) |
[DjVu|PDF] |
| 09:40 | Non-Linear Matrix Factorization Neil D. Lawrence and Raquel Urtasun |
[DjVu|PDF] |
| 10:00 | Training, Adaptation, and Semi-Supervised Learning in a Real-World OCR System Thomas M. Breuel |
[DjVu|PDF] |
| 10:20 | Break | |
| 10:40 | Max Welling On Herding Dynamical Weights and Fractal Geometry |
[DjVu|PDF] |
| 11:20 | Cumulative distribution networks: Graphical models for cumulative distribution functions Jim C. Huang and Brendan J. Frey |
[DjVu|PDF] |
| 11:40 | Emergence of complex like cells in a temporal product network and its smooth generalization Karol Gregor and Yann LeCun |
[DjVu|PDF] |
| 12:00 | Lunch (on your own) | |
| 18:00 | Dinner | |
| 19:30-22:00 | Poster Session A | |
| Wednesday, April 15 | ||
| 08:00 | Breakfast | |
| 09:00 | Oral Session 3 | |
| 09:00 | Probabilistic programs, computability, and de Finetti measures Daniel M. Roy and Cameron E. Freer |
[DjVu|PDF] |
| 09:20 | Kernel Machines Made of DNA Molecules Yung-Kyun Noh and Daniel D. Lee and Cheongtag Kim and Byoung-Tak Zhang |
[DjVu|PDF] |
| 09:40 | Cost-Sensitive Active Visual Category Learning Sudheendra Vijayanarasimhan and Kristen Grauman |
[DjVu|PDF] |
| 10:00 | Towards coherent modeling of scene segmentation, annotation and classification Li-Jia Li and Li Fei-Fei |
[DjVu|PDF] |
| 10:20 | Break | |
| 10:40 | Russ Tedrake Learning to fly like a bird |
[DjVu|PDF] |
| 11:20 | Towards Understanding Situated Text: Concept Labeling, Story Understanding and Weak Supervision Antoine Bordes and Nicolas Usunier and Ronan Collobert and Jason Weston |
[DjVu|PDF] |
| 11:40 | Learning Deep Bolztmann Machines Ruslan Salakhutdinov and Geoffrey Hinton |
[DjVu|PDF] |
| 12:00 | Lunch (on your own) | |
| 18:00 | Dinner | |
| 19:30-22:00 | Poster Session B | |
| Thursday, April 16 | ||
| This is a joint AISTATS 2007 and Learning Workshop day. The oral and poster presentations and the banquet will be together with the Learning Workshop. | ||
| 08:15 | Breakfast | |
| 09:00 | AI-Stats/Learning Oral Session | |
| 09:00 | Scalable Methods for Deep Belief Learning in Very Large Datasets James Philbin and Oliver Williams and Michael Isard |
[DjVu|PDF] |
| 09:20 | Curriculum Learning Yoshua Bengio and Jerome Louradour and Ronan Collobert and Jason Weston |
[DjVu|PDF] |
| 09:40 | High-Accuracy Object Recognition with a New Convolutional Net Architecture and Learning Algorithm Kevin Jarrett, Marc'Aurelio Ranzato, Koray Kavukcuoglu, Yann LeCun |
[DjVu|PDF] |
| 10:00 | Large Scale Online Learning of Image Similarity Through Ranking Gal Chechik and Varun Sharma and Uri Shalit and Samy Bengio |
[DjVu|PDF] |
| 10:20 | Coffee Break | |
| 10:40-12:00 | AI-Stats oral session: probability models | |
| 12:00 | Lunch (on your own) | |
| 16:00-17:15 | AI-Stats oral session: planning and control | |
| 17:15-20:00 | AI-Stats Poster Session I | |
| 20:00 | Learning/Ai-stats Banquet. Speaker: Mark Hanson |