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NLP
2000
14 years 1 months ago
Monte-Carlo Sampling for NP-Hard Maximization Problems in the Framework of Weighted Parsing
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
Jean-Cédric Chappelier, Martin Rajman
ICDT
2009
ACM
119views Database» more  ICDT 2009»
14 years 10 months ago
Analysis of sampling techniques for association rule mining
In this paper, we present a comprehensive theoretical analysis of the sampling technique for the association rule mining problem. Most of the previous works have concentrated only...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Yogi...
ADCM
2010
90views more  ADCM 2010»
13 years 9 months ago
Local reconstruction for sampling in shift-invariant spaces
The local reconstruction from samples is one of most desirable properties for many applications in signal processing, but it has not been given as much attention. In this paper, we...
Qiyu Sun
WWW
2006
ACM
14 years 10 months ago
Random sampling from a search engine's index
We revisit a problem introduced by Bharat and Broder almost a decade ago: how to sample random pages from the corpus of documents indexed by a search engine, using only the search...
Ziv Bar-Yossef, Maxim Gurevich
SUTC
2010
IEEE
13 years 8 months ago
Reordering for Better Compressibility: Efficient Spatial Sampling in Wireless Sensor Networks
—Compressed Sensing (CS) is a novel sampling paradigm that tries to take data-compression concepts down to the sampling layer of a sensory system. It states that discrete compres...
Mohammadreza Mahmudimanesh, Abdelmajid Khelil, Nee...