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» Dynamic power management using machine learning
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ICML
2010
IEEE
15 years 4 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
135
Voted
AAAI
2000
15 years 4 months ago
Inter-Layer Learning Towards Emergent Cooperative Behavior
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even t...
Shawn Arseneau, Wei Sun, Changpeng Zhao, Jeremy R....
129
Voted
ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 3 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
OSDI
2008
ACM
16 years 3 months ago
Hunting for Problems with Artemis
Artemis is a modular application designed for analyzing and troubleshooting the performance of large clusters running datacenter services. Artemis is composed of four modules: (1)...
Gabriela F. Cretu-Ciocarlie, Mihai Budiu, Mois&eac...
142
Voted
EJWCN
2010
157views more  EJWCN 2010»
14 years 10 months ago
Distributed Power Allocation for Parallel Broadcast Channels with Only Common Information in Cognitive Tactical Radio Networks
A tactical radio network is a radio network in which a transmitter broadcasts the same information to its receivers. In this paper, dynamic spectrum management is studied for multi...
Vincent Le Nir, Bart Scheers