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» Bypassing the embedding: algorithms for low dimensional metr...
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ICML
2010
IEEE
14 years 10 months ago
Local Minima Embedding
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Minyoung Kim, Fernando De la Torre
CORR
2007
Springer
122views Education» more  CORR 2007»
14 years 9 months ago
How to Complete a Doubling Metric
In recent years, considerable advances have been made in the study of properties of metric spaces in terms of their doubling dimension. This line of research has not only enhanced...
Anupam Gupta, Kunal Talwar
AAAI
2006
14 years 11 months ago
Embedding Heterogeneous Data Using Statistical Models
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
BIOINFORMATICS
2008
172views more  BIOINFORMATICS 2008»
14 years 9 months ago
Fitting a geometric graph to a protein-protein interaction network
Motivation: Finding a good network null model for protein-protein interaction (PPI) networks is a fundamental issue. Such a model would provide insights into the interplay between...
Desmond J. Higham, Marija Rasajski, Natasa Przulj
ISQED
2005
IEEE
112views Hardware» more  ISQED 2005»
15 years 3 months ago
Two-Dimensional Layout Migration by Soft Constraint Satisfaction
Layout migration has re-emerged as an important task due to the increasing use of library hard intellectual properties. While recent advances of migration tools have accommodated ...
Qianying Tang, Jianwen Zhu