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» A Distance-Based Packing Method for High Dimensional Data
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ICIP
2010
IEEE
13 years 5 months ago
Image analysis with regularized Laplacian eigenmaps
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
Frank Tompkins, Patrick J. Wolfe
SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
13 years 9 months ago
On Point Sampling Versus Space Sampling for Dimensionality Reduction
In recent years, random projection has been used as a valuable tool for performing dimensionality reduction of high dimensional data. Starting with the seminal work of Johnson and...
Charu C. Aggarwal
BMCBI
2008
139views more  BMCBI 2008»
13 years 7 months ago
A topological transformation in evolutionary tree search methods based on maximum likelihood combining p-ECR and neighbor joinin
Background: Inference of evolutionary trees using the maximum likelihood principle is NP-hard. Therefore, all practical methods rely on heuristics. The topological transformations...
Maozu Guo, Jian-Fu Li, Yang Liu
COLING
2010
13 years 2 months ago
Dimensionality Reduction for Text using Domain Knowledge
Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as...
Yi Mao, Krishnakumar Balasubramanian, Guy Lebanon
ICML
2008
IEEE
14 years 8 months ago
An empirical evaluation of supervised learning in high dimensions
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
Rich Caruana, Nikolaos Karampatziakis, Ainur Yesse...