This paper presents an approach that uses special purpose RBAC constraints to base certain access control decisions on context information. In our approach a context constraint is...
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
This paper explores the cognitive limits of estimation in the context of software cost estimation. Two heuristics, representativeness and anchoring, motivate two experiments invol...
Consider an open infrastructure in which anyone can deploy mechanisms to support automated decision making and coordination amongst self-interested computational agents. Strategyp...
The ability to coordinate effectively is critical for agents to accomplish their goals in a multi-agent system. A number of researchers have modeled the coordination problem for m...