We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
The support available in Eclipse to help software developers learn complex APIs and development tools is inadequate; the support is largely passive and the support typically opera...
Izzet Safer, Gail C. Murphy, Julie Waterhouse, Jin...
Shaping can be an effective method for improving the learning rate in reinforcement systems. Previously, shaping has been heuristically motivated and implemented. We provide a for...
We address the problem of learning in repeated N-player (as opposed to 2-player) general-sum games. We describe an extension to existing criteria focusing explicitly on such setti...