Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
This paper takes the first steps towards designing incentive compatible mechanisms for hierarchical decision making problems involving selfish agents. We call these Stackelberg p...
In many settings, a group of agents must come to a joint decision on multiple issues. In practice, this is often done by voting on the issues in sequence. In this paper, we model ...
Abstract. Service-oriented computing has emerged as a new programming paradigm that aims at implementing software applications which can be used through a network via the exchange ...
Abstract. Learning event models from videos has applications ranging from abnormal event detection to content based video retrieval. Relational learning techniques such as Inductiv...
Krishna S. R. Dubba, Anthony G. Cohn, David C. Hog...