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JMLR
2012
13 years 16 hour ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
ISCA
2008
IEEE
137views Hardware» more  ISCA 2008»
15 years 4 months ago
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach
Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deli...
Engin Ipek, Onur Mutlu, José F. Martí...
CDC
2008
IEEE
113views Control Systems» more  CDC 2008»
15 years 4 months ago
Norm optimal Cross-Coupled Iterative Learning Control
— In this paper, we focus on improving contour tracking in precision motion control (PMC) applications through the use of Cross-Coupled Iterative Learning Control (CCILC). Initia...
Kira Barton, Jeroen van de Wijdeven, Andrew Alleyn...
ML
2002
ACM
146views Machine Learning» more  ML 2002»
14 years 9 months ago
Variable Resolution Discretization in Optimal Control
Abstract. The problemof state abstractionis of centralimportancein optimalcontrol,reinforcement learning and Markov decision processes. This paper studies the case of variable reso...
Rémi Munos, Andrew W. Moore
EURONGI
2005
Springer
15 years 3 months ago
An Afterstates Reinforcement Learning Approach to Optimize Admission Control in Mobile Cellular Networks
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
José Manuel Giménez-Guzmán, J...