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» Algorithms for discovering bucket orders from data
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161
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GRC
2008
IEEE
15 years 5 months ago
Neighborhood Smoothing Embedding for Noisy Manifold Learning
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Guisheng Chen, Junsong Yin, Deyi Li
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 11 months ago
Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets
The problem of finding unusual time series has recently attracted much attention, and several promising methods are now in the literature. However, virtually all proposed methods...
Dragomir Yankov, Eamonn J. Keogh, Umaa Rebbapragad...
129
Voted
SODA
1997
ACM
76views Algorithms» more  SODA 1997»
15 years 6 months ago
Markov Chains for Linear Extensions, the Two-Dimensional Case
We study the generation of uniformly distributed linear extensions using Markov chains. In particular we show that monotone coupling from the past can be applied in the case of lin...
Stefan Felsner, Lorenz Wernisch
KDD
2002
ACM
144views Data Mining» more  KDD 2002»
16 years 5 months ago
Efficiently mining frequent trees in a forest
Mining frequent trees is very useful in domains like bioinformatics, web mining, mining semi-structured data, and so on. We formulate the problem of mining (embedded) subtrees in ...
Mohammed Javeed Zaki
147
Voted
ICDCS
2002
IEEE
15 years 9 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...