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ICPR
2008
IEEE
15 years 11 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
IPPS
1998
IEEE
15 years 9 months ago
Memory Space Representation for Heterogeneous Network Process Migration
A major difficulty of heterogeneous process migration is how to collect advanced dynamic data-structures, transform them into machine independent form, and restor them appropriate...
Kasidit Chanchio, Xian-He Sun
185
Voted
ADCM
2011
14 years 12 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 ...
CBMS
1997
IEEE
15 years 9 months ago
3D reconstruction of magnetic resonance imaging using largely spaced slices
This paper presents a full process of reconstruction of magnetic resonance images. The first step is to bring theacquired data fromthefrequencydomain,using a FastFourier Transform...
Agma J. M. Traina, Afonso H. M. A. Prado, Josiane ...
145
Voted
NIPS
2004
15 years 6 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...