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» Learning to Predict User Operations for Adaptive Scheduling
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AAAI
1998
14 years 3 days ago
Learning to Predict User Operations for Adaptive Scheduling
Mixed-initiativesystemspresent the challengeof finding an effective level of interaction betweenhumans and computers. Machinelearning presents a promising approachto this problemi...
Melinda T. Gervasio, Wayne Iba, Pat Langley
WOWMOM
1998
ACM
106views Multimedia» more  WOWMOM 1998»
14 years 3 months ago
A Systems Approach to Prediction, Compensation and Adaptation in Wireless Networks
This paper presents a framework for provisioning application and channel dependent quality of service in wireless networks. The framework is based on three di erent adaptation mec...
Javier Gomez, Andrew T. Campbell, Hiroyuki Morikaw...
AIPS
2006
14 years 5 days ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
GECCO
2004
Springer
179views Optimization» more  GECCO 2004»
14 years 4 months ago
An Evolutionary Meta Hierarchical Scheduler for the Linux Operating System
Abstract. The need for supporting CSCW applications with heterogeneous and varying user requirements calls for adaptive and reconfigurable schedulers accommodating a mixture of re...
Horst Wedde, Muddassar Farooq, Mario Lischka
JSSPP
2005
Springer
14 years 4 months ago
ScoPred-Scalable User-Directed Performance Prediction Using Complexity Modeling and Historical Data
Using historical information to predict future runs of parallel jobs has shown to be valuable in job scheduling. Trends toward more flexible jobscheduling techniques such as adapt...
Benjamin J. Lafreniere, Angela C. Sodan