Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated ...
Alexander Rakhlin, Jacob Abernethy, Peter L. Bartl...
Traditional information systems return answers after a user submits a complete query. Users often feel "left in the dark" when they have limited knowledge about the unde...
Distributed storage systems often use data replication to mask failures and guarantee high data availability. Node failures can be transient or permanent. While the system must ge...
Jing Tian, Zhi Yang, Wei Chen, Ben Y. Zhao, Yafei ...
Any performance evaluation of broadband networks requires modeling of the actual network traffic. Since multimedia services and especially MPEG coded video streams are expected to...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...