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» Using Machine Learning to Focus Iterative Optimization
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IROS
2008
IEEE
115views Robotics» more  IROS 2008»
15 years 8 months ago
A framework for optimal gait generation via learning optimal control using virtual constraint
— This paper proposes an optimal gait generation framework using virtual constraint and learning optimal control. In this method, firstly, we add a constraint by a virtual poten...
Satoshi Satoh, Kenji Fujimoto, Sang-Ho Hyon
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 3 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 2 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
15 years 3 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley
ALT
2006
Springer
15 years 11 months ago
Iterative Learning from Positive Data and Negative Counterexamples
A model for learning in the limit is defined where a (so-called iterative) learner gets all positive examples from the target language, tests every new conjecture with a teacher ...
Sanjay Jain, Efim B. Kinber