Abstract. We consider the problem of scheduling jobs on related machines owned by selfish agents and provide the first deterministic mechanisms with constant approximation that a...
Vincenzo Auletta, Roberto De Prisco, Paolo Penna, ...
We present a new class of randomized approximation algorithms for unrelated parallel machine scheduling problems with the average weighted completion time objective. The key idea i...
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
We study the problem of designing truthful algorithms for scheduling a set of tasks, each one owned by a selfish agent, to a set of parallel (identical or unrelated) machines in or...
We consider the problem of scheduling n jobs that are released over time on a single machine in order to minimize the total ow time. This problem is well-known to be NPcomplete, a...
Hans Kellerer, Thomas Tautenhahn, Gerhard J. Woegi...