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» Distributed data mining in grid computing environments
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IPPS
2010
IEEE
15 years 7 days ago
Attack-resistant frequency counting
We present collaborative peer-to-peer algorithms for the problem of approximating frequency counts for popular items distributed across the peers of a large-scale network. Our alg...
Bo Wu, Jared Saia, Valerie King
ICAI
2004
15 years 3 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
PKDD
2005
Springer
164views Data Mining» more  PKDD 2005»
15 years 7 months ago
Clustering and Prediction of Mobile User Routes from Cellular Data
Location-awareness and prediction of future locations is an important problem in pervasive and mobile computing. In cellular systems (e.g., GSM) the serving cell is easily availabl...
Kari Laasonen
VLDB
1998
ACM
192views Database» more  VLDB 1998»
15 years 6 months ago
Algorithms for Mining Distance-Based Outliers in Large Datasets
This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Edwin M. Knorr, Raymond T. Ng
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 21 days ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup