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IJON
2010
120views more  IJON 2010»
13 years 6 months ago
Semi-supervised learning with varifold Laplacians
This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
Lei Ding, Peibiao Zhao
ADCM
2011
13 years 2 months ago
Convergence and smoothness analysis of subdivision rules in Riemannian and symmetric spaces
After a discussion on definability of invariant subdivision rules we discuss rules for sequential data living in Riemannian manifolds and in symmetric spaces, having in mind the s...
Johannes Wallner, Esfandiar Nava Yazdani, Andreas ...
ICCV
2007
IEEE
14 years 1 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
NIPS
2001
13 years 9 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
EDBT
2009
ACM
208views Database» more  EDBT 2009»
14 years 2 months ago
Flexible and efficient querying and ranking on hyperlinked data sources
There has been an explosion of hyperlinked data in many domains, e.g., the biological Web. Expressive query languages and effective ranking techniques are required to convert this...
Ramakrishna Varadarajan, Vagelis Hristidis, Louiqa...