Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Today's networking community is becoming increasingly skeptical of the significance of research results founded wholly upon experimental results conducted in simulation. Now, ...
Jeffrey Considine, John W. Byers, Ketan Meyer-Pate...
Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses. The set of diagnoses can be reduced by taking into account extra observations (passive mon...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
Memory management is a fundamental problem in computer architecture and operating systems. We consider a two-level memory system with fast, but small cache and slow, but large mai...