Here are a few of presentations interesting me at the snowbird learning workshop (which, amusingly, was in Florida with AIStat).
- Thomas Breuel described machine learning problems within OCR and an open source OCR software/research platform with modular learning components as well has a 60Million size dataset derived from Google‘s scanned books.
- Kristen Grauman and Fei-Fei Li discussed using active learning with different cost labels and large datasets for image ontology. Both of them used Mechanical Turk as a labeling system, which looks to become routine, at least for vision problems.
- Russ Tedrake discussed using machine learning for control, with a basic claim that it was the way to go for problems involving a medium Reynold’s number such as in bird flight, where simulation is extremely intense.
- Yann LeCun presented a poster on an FPGA for convolutional neural networks yielding a factor of 100 speedup in processing. In addition to the graphics processor approach Rajat has worked on, this seems like an effective approach to deal with the need to compute many dot products.