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» On learning with dissimilarity functions
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IWINAC
2007
Springer
16 years 22 days ago
Requirements for Machine Lifelong Learning
A significant advance in inductive modelling are systems that retain learned knowledge and selectively transfer portions of that knowledge as a source of inductive bias. We defi...
Daniel L. Silver, Ryan Poirier
ERLANG
2007
ACM
15 years 10 months ago
Learning programming with Erlang
This paper presents an interactive framework for pupils to learn the basic concepts of programming by means of the functional programming language Erlang. Beside the idea of the f...
Frank Huch
ECML
2006
Springer
15 years 10 months ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
JMLR
2010
198views more  JMLR 2010»
15 years 5 months ago
On Learning with Integral Operators
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito
ICANN
2011
Springer
14 years 10 months ago
Learning Curves for Gaussian Processes via Numerical Cubature Integration
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
Simo Särkkä