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SBACPAD
2005
IEEE
176views Hardware» more  SBACPAD 2005»
14 years 1 months ago
Analyzing and Improving Clustering Based Sampling for Microprocessor Simulation
The time required to simulate a complete benchmark program using the cycle-accurate model of a microprocessor can be prohibitively high. One of the proposed methodologies, represe...
Yue Luo, Ajay Joshi, Aashish Phansalkar, Lizy Kuri...
DBISP2P
2008
Springer
124views Database» more  DBISP2P 2008»
13 years 9 months ago
Exploiting Distribution Skew for Scalable P2P Text Clustering
K-Means clustering is widely used in information retrieval and data mining. Distributed K-Means variants have already been proposed, but none of the past algorithms scales to large...
Odysseas Papapetrou, Wolf Siberski, Fabian Leitrit...
IEEEVAST
2010
13 years 2 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
WSDM
2009
ACM
172views Data Mining» more  WSDM 2009»
14 years 2 months ago
Clustering the tagged web
Automatically clustering web pages into semantic groups promises improved search and browsing on the web. In this paper, we demonstrate how user-generated tags from largescale soc...
Daniel Ramage, Paul Heymann, Christopher D. Mannin...
ICDM
2005
IEEE
271views Data Mining» more  ICDM 2005»
14 years 1 months ago
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the r...
Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu