We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
We address the problems of I/O scheduling and buffer management for general reference strings in a parallel I/O system. Using the standard parallel disk model withD disks and a sh...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Abstract. We investigate the online exploration problem of a shortsighted mobile robot moving in an unknown cellular room without obstacles. The robot has a very limited sensor; it...
Christian Icking, Thomas Kamphans, Rolf Klein, Elm...
In this paper, we propose a stochastic model to describe how search service providers charge client companies based on users' queries for the keywords related to these compan...