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» Multiagent learning using a variable learning rate
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CDC
2010
IEEE
196views Control Systems» more  CDC 2010»
14 years 4 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
2007
Springer
168views Optimization» more  GECCO 2007»
15 years 3 months ago
Empirical analysis of generalization and learning in XCS with gradient descent
We analyze generalization and learning in XCS with gradient descent. At first, we show that the addition of gradient in XCS may slow down learning because it indirectly decreases...
Pier Luca Lanzi, Martin V. Butz, David E. Goldberg
NIPS
2004
14 years 11 months ago
Rate- and Phase-coded Autoassociative Memory
Areas of the brain involved in various forms of memory exhibit patterns of neural activity quite unlike those in canonical computational models. We show how to use well-founded Ba...
Máté Lengyel, Peter Dayan
UAI
2003
14 years 11 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
IJCAI
2007
14 years 11 months ago
WiFi-SLAM Using Gaussian Process Latent Variable Models
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor l...
Brian Ferris, Dieter Fox, Neil D. Lawrence