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COLT
2005
Springer
14 years 1 months ago
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...
Mikhail Belkin, Partha Niyogi

Book
498views
15 years 5 months ago
Machine Learning, Neural and Statistical Classification
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks Methods ...
Ellis Horwood
JMLR
2010
123views more  JMLR 2010»
13 years 2 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
ICDAR
2005
IEEE
14 years 1 months ago
Language Identification of Character Images Using Machine Learning Techniques
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
Ying-Ho Liu, Fu Chang, Chin-Chin Lin
ICML
2007
IEEE
14 years 8 months ago
A recursive method for discriminative mixture learning
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Minyoung Kim, Vladimir Pavlovic