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ILP
1998
Springer
15 years 6 months ago
Strongly Typed Inductive Concept Learning
In this paper we argue that the use of a language with a type system, together with higher-order facilities and functions, provides a suitable basis for knowledge representation in...
Peter A. Flach, Christophe G. Giraud-Carrier, John...
87
Voted
ICPR
2008
IEEE
16 years 3 months ago
On refining dissimilarity matrices for an improved NN learning
Application-specific dissimilarity functions can be used for learning from a set of objects represented by pairwise dissimilarity matrices in this context. These dissimilarities m...
Elzbieta Pekalska, Robert P. W. Duin
AAAI
2012
13 years 5 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
111
Voted
ICML
2006
IEEE
16 years 3 months ago
A DC-programming algorithm for kernel selection
We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
129
Voted
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 6 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass