- 7:30 -- 7:40 Introduction, Organizers
- 7:40 -- 8:20 Noah Smith:
Approximate Inference in Natural Language Processing.
- 8:20 -- 9:00 Ben Taskar:
Structured Prediction Cascades.
- 9:00 -- 9:10 Coffee Break.
- 9:10 -- 9:50 Eric Xing:
Jointly Maximum Margin and Maximum Entropy Learning of Graphical Models.
- 9:50 -- 10:30 Pedro Domingos:
Large-Scale Learning and Inference: What We Have Learned
with Markov Logic Networks.
- 3:30 -- 4:00 Pawan Kumar:
Parameter Learning using Approximate MAP Inference.
- 4:00 -- 4:40 David McAllester:
Training Structured Predictors for Novel Loss Functions.
- 4:40 -- 5:10 Bill Freeman:
Some machine learning problems that we in the computer vision
community would like to see solved.
- 5:10 -- 5:20 Coffee Break.
- 5:20 -- 6:00 Geoffrey Hinton:
Image Retrieval using Short Binary Codes.
- 6:00 -- 6:30 Discussion and Conclusions, Organizers
Morning Session: 7:30 - 10:30
Afternoon Session: 3:30 - 6:30