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» Dynamic power management using machine learning
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ML
2002
ACM
167views Machine Learning» more  ML 2002»
15 years 4 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
JMLR
2010
145views more  JMLR 2010»
14 years 11 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
SGAI
2009
Springer
15 years 11 months ago
Explaining How to Play Real-Time Strategy Games
Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them a...
Ronald A. Metoyer, Simone Stumpf, Christoph Neuman...
CISS
2008
IEEE
15 years 11 months ago
Achievable rates and training optimization for fading relay channels with memory
—In this paper, transmission over time-selective, flat fading relay channels is studied. It is assumed that channel fading coefficients are not known a priori. Transmission tak...
Sami Akin, Mustafa Cenk Gursoy
121
Voted
ICCD
2007
IEEE
100views Hardware» more  ICCD 2007»
16 years 2 months ago
VOSCH: Voltage scaled cache hierarchies
The cache hierarchy of state-of-the-art—especially multicore—microprocessors consumes a significant amount of area and energy. A significant amount of research has been devo...
Weng-Fai Wong, Cheng-Kok Koh, Yiran Chen, Hai Li