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GECCO
2008
Springer
170views Optimization» more  GECCO 2008»
13 years 8 months ago
Evolving prediction weights using evolution strategy
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
Trung Hau Tran, Cédric Sanza, Yves Duthen
CDC
2010
IEEE
196views Control Systems» more  CDC 2010»
13 years 2 months ago
Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Vladislav B. Tadic
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
COLT
1992
Springer
13 years 11 months ago
On the Computational Power of Neural Nets
This paper deals with finite size networks which consist of interconnections of synchronously evolving processors. Each processor updates its state by applying a "sigmoidal&q...
Hava T. Siegelmann, Eduardo D. Sontag
NPL
1998
175views more  NPL 1998»
13 years 7 months ago
Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
Roman Rosipal, Milos Koska, Igor Farkas