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GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
15 years 9 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
TKDE
2008
154views more  TKDE 2008»
15 years 4 months ago
Analyzing the Structure and Evolution of Massive Telecom Graphs
Abstract-- With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customer...
Amit Anil Nanavati, Rahul Singh, Dipanjan Chakrabo...
TWC
2008
130views more  TWC 2008»
15 years 4 months ago
On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance
We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elli...
Qing Zhao, Bhaskar Krishnamachari, Keqin Liu
ICONFERENCE
2011
14 years 11 months ago
The structure of collaborative problem solving in a virtual math team
To develop a science of small-group interaction in groupware, we need a method for analyzing the structure of computer-mediated discourse. Conversation analysis offers an analysis...
Gerry Stahl
EMNLP
2011
14 years 4 months ago
Universal Morphological Analysis using Structured Nearest Neighbor Prediction
In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly o...
Young-Bum Kim, João Graça, Benjamin ...