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COLT
2008
Springer
13 years 9 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale
STACS
2004
Springer
14 years 29 days ago
Optimal and Online Preemptive Scheduling on Uniformly Related Machines
We consider the problem of preemptive scheduling on uniformly related machines. We present a semi-online algorithm which, if the optimal makespan is given in advance, produces an ...
Tomás Ebenlendr, Jiri Sgall
WAOA
2004
Springer
132views Algorithms» more  WAOA 2004»
14 years 29 days ago
Stochastic Online Scheduling on Parallel Machines
We consider a non-preemptive, stochastic parallel machine scheduling model with the goal to minimize the weighted completion times of jobs. In contrast to the classical stochastic ...
Nicole Megow, Marc Uetz, Tjark Vredeveld
ICMAS
1998
13 years 9 months ago
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and comp...
Wilfried Brauer, Gerhard Weiß
COR
2006
86views more  COR 2006»
13 years 7 months ago
Minimizing the earliness-tardiness costs on a single machine
In this paper the one-machine scheduling problem with linear earliness and tardiness costs is considered. The7 cost functions are job dependent and asymmetric. The problem consist...
Jakub Bauman, Joanna Józefowska