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» Iterative Learning Control - Monotonicity and Optimization
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113
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GECCO
2004
Springer
115views Optimization» more  GECCO 2004»
15 years 8 months ago
Robotic Control Using Hierarchical Genetic Programming
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canon...
Marcin L. Pilat, Franz Oppacher
152
Voted
IEEEPACT
2008
IEEE
15 years 9 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
144
Voted
IJCAI
2007
15 years 4 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell
132
Voted
ATAL
2004
Springer
15 years 8 months ago
Adaptive, Distributed Control of Constrained Multi-Agent Systems
Product Distribution (PD) theory was recently developed as a framework for analyzing and optimizing distributed systems. In this paper we demonstrate its use for adaptive distribu...
Stefan Bieniawski, David Wolpert
107
Voted
CDC
2009
IEEE
113views Control Systems» more  CDC 2009»
15 years 7 months ago
Distributed and optimal reduced primal-dual algorithm for uplink OFDM resource allocation
— Orthogonal frequency division multiplexing (OFDM) is the key component of many emerging broadband wireless access standards. The resource allocation in OFDM uplink, however, is...
Xiao-Xin Zhang, Liang Chen, Jianwei Huang, Minghua...