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» Adaptive Bound Optimization for Online Convex Optimization
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COLT
2008
Springer
13 years 9 months ago
Regret Bounds for Sleeping Experts and Bandits
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yo...
ICML
2009
IEEE
14 years 8 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
GLVLSI
2010
IEEE
172views VLSI» more  GLVLSI 2010»
14 years 23 days ago
Online convex optimization-based algorithm for thermal management of MPSoCs
Meeting the temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. The goal of thermal mana...
Francesco Zanini, David Atienza, Giovanni De Miche...
CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
14 years 2 months ago
A proximal center-based decomposition method for multi-agent convex optimization
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
Ion Necoara, Johan A. K. Suykens
JCO
2006
96views more  JCO 2006»
13 years 7 months ago
One-dimensional optimal bounded-shape partitions for Schur convex sum objective functions
Consider the problem of partitioning n nonnegative numbers into p parts, where part i can be assigned ni numbers with ni lying in a given range. The goal is to maximize a Schur con...
F. H. Chang, H. B. Chen, J. Y. Guo, Frank K. Hwang...