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IJCAI
1997
13 years 8 months ago
An Effective Learning Method for Max-Min Neural Networks
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
Loo-Nin Teow, Kia-Fock Loe
GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
14 years 1 months ago
Exploring the behavior of building blocks for multi-objective variation operator design using predator-prey dynamics
In this paper, we utilize a predator-prey model in order to identify characteristics of single-objective variation operators in the multi-objective problem domain. In detail, we a...
Christian Grimme, Joachim Lepping, Alexander Papas...
SIGMETRICS
2011
ACM
191views Hardware» more  SIGMETRICS 2011»
12 years 10 months ago
Stability analysis of QCN: the averaging principle
Data Center Networks have recently caused much excitement in the industry and in the research community. They represent the convergence of networking, storage, computing and virtu...
Mohammad Alizadeh, Abdul Kabbani, Berk Atikoglu, B...
WSDM
2010
ACM
168views Data Mining» more  WSDM 2010»
14 years 2 months ago
Evolution of two-sided markets
Two-sided markets arise when two diļ¬€erent types of users may realize gains by interacting with one another through one or more platforms or mediators. We initiate a study of the...
Ravi Kumar, Yury Lifshits, Andrew Tomkins
CEC
2005
IEEE
14 years 1 months ago
Dynamic niching in evolution strategies with covariance matrix adaptation
Abstract- Evolutionary Algorithms (EAs) have the tendency to converge quickly into a single solution in the search space. However, many complex search problems require the identiļ¬...
Ofer M. Shir, Thomas Bäck