We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Mapping problem-space features into solution-space features is a fundamental configuration problem in software product line engineering. A configuration problem is defined as g...
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
: This paper describes an application of a machine-learning agent, SimStudent, as a teachable peer learner that allows a student to learn by teaching. SimStudent has been integrate...
Noboru Matsuda, Evelyn Yarzebinski, Victoria Keise...
We address the problem of designing distributed algorithms for large scale networks that are robust to Byzantine faults. We consider a message passing, full information model: the ...
Valerie King, Steven Lonargan, Jared Saia, Amitabh...