Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
This paper describes the adaptation of a modern compiler construction course to target an FPGA-based hardware platform used throughout our computer science curriculum. One of the ...
Motivated by a machine learning perspective—that gametheoretic equilibria constraints should serve as guidelines for predicting agents’ strategies, we introduce maximum causal...
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...