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» Parameterized Learning Complexity
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119
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CEC
2005
IEEE
15 years 5 months ago
Co-evolutionary modular neural networks for automatic problem decomposition
Abstract- Decomposing a complex computational problem into sub-problems, which are computationally simpler to solve individually and which can be combined to produce a solution to ...
Vineet R. Khare, Xin Yao, Bernhard Sendhoff, Yaoch...
138
Voted
IADIS
2008
15 years 5 months ago
Data Mining Applications in Intelligent Integrated Development Environments
Programming and developing of small scale software applications can be accomplished with simple command-line compilers that can be used to compile, test, and execute code generati...
Ali Farahmand Nejad, Shahabedin Bayati, Sadegh Kha...
121
Voted
NIPS
2007
15 years 5 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
NIPS
2007
15 years 5 months ago
Consistent Minimization of Clustering Objective Functions
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Ulrike von Luxburg, Sébastien Bubeck, Stefa...
127
Voted
UAI
2000
15 years 5 months ago
PEGASUS: A policy search method for large MDPs and POMDPs
We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...
Andrew Y. Ng, Michael I. Jordan