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ICASSP
2008
IEEE
16 years 1 months ago
Learning to satisfy
This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
IJCAI
1989
15 years 8 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
ICANN
2005
Springer
16 years 7 days ago
Action Understanding and Imitation Learning in a Robot-Human Task
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...
Wolfram Erlhagen, Albert Mukovskiy, Estela Bicho, ...
COLT
2003
Springer
15 years 12 months ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
ICIAP
1999
ACM
15 years 11 months ago
Learning Visual Operators from Examples: A New Paradigm in Image Processing
This paper presents a general strategy for designing efficient visual operators. The approach is highly task oriented and what constitutes the relevant information is defined by...
Hans Knutsson, Magnus Borga