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» Perceptual Learning and Abstraction in Machine Learning
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SBIA
2004
Springer
15 years 3 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
EKAW
2008
Springer
14 years 11 months ago
Learning Disjointness for Debugging Mappings between Lightweight Ontologies
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
Christian Meilicke, Johanna Völker, Heiner St...
BMCBI
2008
228views more  BMCBI 2008»
14 years 9 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
SAGA
2009
Springer
15 years 4 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
ICPR
2008
IEEE
15 years 11 months 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,...