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PR
2007
81views more  PR 2007»
13 years 7 months ago
Mining evolving data streams for frequent patterns
A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this pape...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...

Lecture Notes
488views
15 years 6 months ago
Econometrics
These notes cover several topics such as Univariate Time Series Analysis, The Distribution of a Sample Average, Least Squares, Instrumental Variable Method, Simulating the Finite S...
Paul Söderlind
BIOINFORMATICS
2005
93views more  BIOINFORMATICS 2005»
13 years 7 months ago
Donuts, scratches and blanks: robust model-based segmentation of microarray images
Inner holes, artifacts and blank spots are common in microarray images, but current image analysis methods do not pay them enough attention. We propose a new robust model-based me...
Qunhua Li, Chris Fraley, Roger Eugene Bumgarner, K...
ICWN
2003
13 years 9 months ago
Localization in Wireless Sensor Networks: A Probabilistic Approach
— In this paper we consider a probabilistic approach to the problem of localization in wireless sensor networks and propose a distributed algorithm that helps unknown nodes to de...
Vaidyanathan Ramadurai, Mihail L. Sichitiu
SIGMOD
2006
ACM
219views Database» more  SIGMOD 2006»
14 years 7 months ago
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Flip Korn, S. Muthukrishnan, Yihua Wu