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» Adaptive Algorithms for Online Decision Problems
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ALT
2005
Springer
14 years 4 months ago
Defensive Universal Learning with Experts
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
Jan Poland, Marcus Hutter
AAAI
2007
13 years 10 months ago
Restart Schedules for Ensembles of Problem Instances
The mean running time of a Las Vegas algorithm can often be dramatically reduced by periodically restarting it with a fresh random seed. The optimal restart schedule depends on th...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
SOFSEM
2010
Springer
14 years 4 months ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour
EWRL
2008
13 years 9 months ago
Markov Decision Processes with Arbitrary Reward Processes
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
Jia Yuan Yu, Shie Mannor, Nahum Shimkin
CLUSTER
2002
IEEE
13 years 7 months ago
Online Prediction of the Running Time of Tasks
Abstract. We describe and evaluate the Running Time Advisor (RTA), a system that can predict the running time of a compute-bound task on a typical shared, unreserved commodity host...
Peter A. Dinda