We use the idea of dependence balance to obtain a new outer bound for the capacity region of the discrete memoryless multiple-access channel with noiseless feedback (MAC-FB). We co...
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...
In cryptography, there has been tremendous success in building primitives out of homomorphic semantically-secure encryption schemes, using homomorphic properties in a blackbox way...
We introduce a new state discrimination problem in which we are given additional information about the state after the measurement, or more generally, after a quantum memory bound ...
Manuel A. Ballester, Stephanie Wehner, Andreas Win...
The use of caches poses a difficult tradeoff for architects of real-time systems. While caches provide significant performance advantages, they have also been viewed as inherently...
Robert D. Arnold, Frank Mueller, David B. Whalley,...