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ALT
2006
Springer
16 years 2 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
2008
Springer
121views Optimization» more  GECCO 2008»
15 years 6 months ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor
WWW
2008
ACM
16 years 6 months ago
Why web 2.0 is good for learning and for research: principles and prototypes
The term "Web 2.0" is used to describe applications that distinguish themselves from previous generations of software by a number of principles. Existing work shows that...
Carsten Ullrich, Kerstin Borau, Heng Luo, Xiaohong...
WETICE
2008
IEEE
15 years 12 months ago
An Architecture for an Adaptive and Collaborative Learning Management System in Aviation Security
The importance of aviation security has increased dramatically in recent years. Frequently changing regulations and the need to adapt quickly to new and emerging threats are chall...
Yi Guo, Adrian Schwaninger, Harald Gall
COLT
2010
Springer
15 years 3 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha