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» Approximation Algorithms for Scheduling on Multiple Machines
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ICML
2007
IEEE
14 years 8 months ago
Automatic shaping and decomposition of reward functions
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
Bhaskara Marthi
MASCOTS
2001
13 years 9 months ago
Large-Scale Simulation of Replica Placement Algorithms for a Serverless Distributed File System
Farsite is a scalable, distributed file system that logically functions as a centralized file server but that is physically implemented on a set of client desktop computers. Farsi...
John R. Douceur, Roger Wattenhofer
RTAS
1999
IEEE
13 years 12 months ago
Scalable Scheduling Support for Loss and Delay Constrained Media Streams
Real-time media servers need to service hundreds and, possibly, thousands of clients, each with their own quality of service (QoS) requirements. To guarantee such diverse QoS requ...
Richard West, Karsten Schwan, Christian Poellabaue...
OSDI
2008
ACM
14 years 8 months ago
Improving MapReduce Performance in Heterogeneous Environments
MapReduce is emerging as an important programming model for large-scale data-parallel applications such as web indexing, data mining, and scientific simulation. Hadoop is an open-...
Matei Zaharia, Andy Konwinski, Anthony D. Joseph, ...
ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson