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» Approximate algorithms for neural-Bayesian approaches
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STOC
2003
ACM
140views Algorithms» more  STOC 2003»
15 years 10 months ago
Approximation schemes for clustering problems
We present a general approach for designing approximation algorithms for a fundamental class of geometric clustering problems in arbitrary dimensions. More specifically, our appro...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 13 days ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
ICALP
2005
Springer
15 years 3 months ago
New Approaches for Virtual Private Network Design
Virtual Private Network Design is the following NP-hard problem. We are given a communication network, represented as a weighted graph with thresholds on the nodes which represent...
Friedrich Eisenbrand, Fabrizio Grandoni, Gianpaolo...
ICASSP
2008
IEEE
15 years 4 months ago
Identification of linear systems with adaptive control of the cross-multiplicative transfer function approximation
In this paper, we extend the cross-multiplicative transfer function (CMTF) approach for improved system identification in the shorttime Fourier transform (STFT) domain. The propo...
Yekutiel Avargel, Israel Cohen
STOC
2003
ACM
164views Algorithms» more  STOC 2003»
15 years 10 months ago
Approximate counting by dynamic programming
We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to pro...
Martin E. Dyer