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» Strong Separation of Learning Classes
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EUROCOLT
1999
Springer
13 years 11 months ago
Query by Committee, Linear Separation and Random Walks
Abstract. Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algori...
Ran Bachrach, Shai Fine, Eli Shamir
COCO
2003
Springer
85views Algorithms» more  COCO 2003»
14 years 19 days ago
Universal Languages and the Power of Diagonalization
We define and study strong diagonalization and compare it to weak diagonalization, implicit in [7]. Kozen’s result in [7] shows that virtually every separation can be recast as...
Alan Nash, Russell Impagliazzo, Jeffrey B. Remmel
ALT
2006
Springer
14 years 4 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
Improving GP classifier generalization using a cluster separation metric
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Ashley George, Malcolm I. Heywood
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen