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TSMC
2010
13 years 1 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
13 years 8 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
SCAM
2006
IEEE
14 years 26 days ago
Constructing Accurate Application Call Graphs For Java To Model Library Callbacks
Call graphs are widely used to represent calling relationships among methods. However, there is not much interest in calling relationships among library methods in many software e...
Weilei Zhang, Barbara G. Ryder
ICALP
2011
Springer
12 years 10 months ago
Steiner Transitive-Closure Spanners of Low-Dimensional Posets
Given a directed graph G = (V, E) and an integer k ≥ 1, a Steiner k-transitive-closure-spanner (Steiner k-TC-spanner) of G is a directed graph H = (VH , EH ) such that (1) V ⊆ ...
Piotr Berman, Arnab Bhattacharyya, Elena Grigoresc...
CIKM
2003
Springer
14 years 3 days ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu