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GECCO
2008
Springer
147views Optimization» more  GECCO 2008»
15 years 4 months ago
On selecting the best individual in noisy environments
In evolutionary algorithms, the typical post-processing phase involves selection of the best-of-run individual, which becomes the final outcome of the evolutionary run. Trivial f...
Wojciech Jaskowski, Wojciech Kotlowski
FOCM
2006
97views more  FOCM 2006»
15 years 3 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
TSMC
2008
146views more  TSMC 2008»
15 years 3 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
JAIR
1998
198views more  JAIR 1998»
15 years 3 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
SIGMETRICS
2002
ACM
128views Hardware» more  SIGMETRICS 2002»
15 years 3 months ago
High-density model for server allocation and placement
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Craig W. Cameron, Steven H. Low, David X. Wei