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KDD
2001
ACM
187views Data Mining» more  KDD 2001»
14 years 10 months ago
Random projection in dimensionality reduction: applications to image and text data
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
Ella Bingham, Heikki Mannila
STOC
2003
ACM
95views Algorithms» more  STOC 2003»
14 years 10 months ago
Random knapsack in expected polynomial time
In this paper, we present the first average-case analysis proving an expected polynomial running time for an exact algorithm for the 0/1 knapsack problem. In particular, we prove,...
René Beier, Berthold Vöcking
KELSI
2004
Springer
14 years 3 months ago
A Randomized Algorithm for Distance Matrix Calculations in Multiple Sequence Alignment
Multiple sequence alignment (MSA) is a vital problem in biology. Optimal alignment of multiple sequences becomes impractical even for a modest number of sequences [1] since the gen...
Sanguthevar Rajasekaran, Vishal Thapar, Hardik Dav...
SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
13 years 11 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
APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
13 years 12 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan