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ICML
2009
IEEE
15 years 10 months ago
Learning when to stop thinking and do something!
An anytime algorithm is capable of returning a response to the given task at essentially any time; typically the quality of the response improves as the time increases. Here, we c...
Barnabás Póczos, Csaba Szepesv&aacut...
ATAL
2008
Springer
14 years 11 months ago
Evaluating the performance of DCOP algorithms in a real world, dynamic problem
Complete algorithms have been proposed to solve problems modelled as distributed constraint optimization (DCOP). However, there are only few attempts to address real world scenari...
Robert Junges, Ana L. C. Bazzan
MFCS
2004
Springer
15 years 3 months ago
Optimal Preemptive Scheduling for General Target Functions
We study the problem of optimal preemptive scheduling with respect to a general target function. Given n jobs with associated weights and m ≤ n uniformly related machines, one a...
Leah Epstein, Tamir Tassa
CP
1997
Springer
15 years 1 months ago
Five Pitfalls of Empirical Scheduling Research
A number of pitfalls of empirical scheduling research are illustrated using real experimental data. These pitfalls, in general, serve to slow the progress of scheduling research b...
J. Christopher Beck, Andrew J. Davenport, Mark S. ...
CLUSTER
2008
IEEE
15 years 4 months ago
Divisible load scheduling with improved asymptotic optimality
—Divisible load model allows scheduling algorithms that give nearly optimal makespan with practical computational complexity. Beaumont et al. have shown that their algorithm prod...
Reiji Suda