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ICML
2003
IEEE
14 years 7 months ago
Cross-Entropy Directed Embedding of Network Data
We present a novel approach to embedding data represented by a network into a lowdimensional Euclidean space. Unlike existing methods, the proposed method attempts to minimize an ...
Takeshi Yamada, Kazumi Saito, Naonori Ueda
TALG
2008
86views more  TALG 2008»
13 years 7 months ago
Embeddings of negative-type metrics and an improved approximation to generalized sparsest cut
In this paper, we study the metrics of negative type, which are metrics (V, d) such that d is an Euclidean metric; these metrics are thus also known as " 2-squared" met...
Shuchi Chawla, Anupam Gupta, Harald Räcke
ARSCOM
2005
94views more  ARSCOM 2005»
13 years 7 months ago
Isometrically Embedded Graphs
Can an arbitrary graph be embedded in Euclidean space so that the isometry group of its vertex set is precisely its graph automorphism group? This paper gives an affirmative answe...
Debra L. Boutin
ECCV
2006
Springer
14 years 9 months ago
An Intensity Similarity Measure in Low-Light Conditions
In low-light conditions, it is known that Poisson noise and quantization noise become dominant sources of noise. While intensity difference is usually measured by Euclidean distanc...
François Alter, Yasuyuki Matsushita, Xiaoou...
ISVC
2010
Springer
13 years 5 months ago
Markov Random Field-Based Clustering for the Integration of Multi-view Range Images
Abstract. Multi-view range image integration aims at producing a single reasonable 3D point cloud. The point cloud is likely to be inconsistent with the measurements topologically ...
Ran Song, Yonghuai Liu, Ralph R. Martin, Paul L. R...