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ICML
2009
IEEE
16 years 5 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
WWW
2004
ACM
16 years 5 months ago
Ontological representation of learning objects: building interoperable vocabulary and structures
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Jian Qin, Naybell Hernández
ECML
2006
Springer
15 years 8 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
ICALT
2003
IEEE
15 years 9 months ago
An Intelligent Tutoring System Prototype for Learning to Program Java?
The “JavaTM Intelligent Tutoring System” (JITS) research project involves the development of a programming tutor designed for students in their first programming course in Jav...
Edward R. Sykes
CORR
2006
Springer
130views Education» more  CORR 2006»
15 years 4 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...