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» On Optimal Learning Algorithms for Multiplicity Automata
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ECML
2006
Springer
15 years 3 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
ICPR
2010
IEEE
15 years 3 months ago
Localized Multiple Kernel Regression
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
Mehmet Gönen, Ethem Alpaydin
GECCO
2003
Springer
124views Optimization» more  GECCO 2003»
15 years 4 months ago
Using an Immune System Model to Explore Mate Selection in Genetic Algorithms
Abstract. When Genetic Algorithms (GAs) are employed in multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulation...
Chien-Feng Huang
AIPS
2006
15 years 1 months ago
Optimal STRIPS Planning by Maximum Satisfiability and Accumulative Learning
Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potenti...
Zhao Xing, Yixin Chen, Weixiong Zhang
ICPR
2008
IEEE
16 years 27 days ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...