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» The Localization Hypothesis and Machines
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ICML
2006
IEEE
16 years 19 days ago
Locally adaptive classification piloted by uncertainty
Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
ICML
2007
IEEE
16 years 19 days ago
Local learning projections
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...
Bernhard Schölkopf, Kai Yu, Mingrui Wu, Shipe...
ICML
2007
IEEE
16 years 19 days ago
Map building without localization by dimensionality reduction techniques
This paper proposes a new map building framework for mobile robot named Localization-Free Mapping by Dimensionality Reduction (LFMDR). In this framework, the robot map building is...
Takehisa Yairi
ECML
2007
Springer
15 years 6 months ago
Neighborhood-Based Local Sensitivity
Abstract. We introduce a nonparametric model for sensitivity estimation which relies on generating points similar to the prediction point using its k nearest neighbors. Unlike most...
Paul N. Bennett
78
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MLDM
2001
Springer
15 years 4 months ago
Local Learning Framework for Recognition of Lowercase Handwritten Characters
Abstract. This paper proposes a general local learning framework to effectively alleviate the complexities of classifier design by means of “divide and conquer” principle and ...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen