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» On the Convergence of Bound Optimization Algorithms
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PIMRC
2008
IEEE
16 years 25 days ago
Distributed network utility optimization in wireless sensor networks using power control
—We extend the existing network utility maximization (NUM) framework for wired networks to wireless sensor networks by formulating it in order to take into account interference a...
George Tichogiorgos, Kin K. Leung, Archan Misra, T...
FOCM
2007
94views more  FOCM 2007»
15 years 6 months ago
Trust-Region Methods on Riemannian Manifolds
A general scheme for trust-region methods on Riemannian manifolds is proposed and analyzed. Among the various approaches available to (approximately) solve the trust-region subpro...
Pierre-Antoine Absil, C. G. Baker, Kyle A. Galliva...
ISDA
2008
IEEE
16 years 26 days ago
Inertia-Adaptive Particle Swarm Optimizer for Improved Global Search
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updati...
Kaushik Suresh, Sayan Ghosh, Debarati Kundu, Abhir...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
15 years 10 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
UAI
2001
15 years 7 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao