72 search results - page 11 / 15 » Learning Heuristic Functions through Approximate Linear Prog... |
JMLR
2010
13 years 2 months ago
2010
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
CISS
2007
IEEE
13 years 11 months ago
2007
IEEE
Abstract-Joint subcarrier, power and rate allocation in orthogonal frequency division multiple access (OFDMA) scheduling is investigated for both downlink and uplink wireless trans...
4OR
2010
13 years 6 months ago
2010
This a summary of the author's PhD thesis supervised by Leo Liberti, Philippe Baptiste and Daniel Krob and defended on 18 June 2009 at Ecole Polytechnique, Palaiseau, France. ...
AI
1998
Springer
13 years 7 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
CGO
2007
IEEE
14 years 1 months ago
2007
IEEE
This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program perform...