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HPCN
1999
Springer
15 years 1 months ago
Data Intensive Distributed Computing; A Medical Application Example
Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data from around the world, as well as employing large-scale computation. The...
Jason Lee, Brian Tierney, William E. Johnston
93
Voted
FGCS
2000
143views more  FGCS 2000»
14 years 9 months ago
A data intensive distributed computing architecture for "Grid" applications
Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data from around the world, as well as employing large-scale computation. The...
Brian Tierney, William E. Johnston, Jason Lee, Mar...
100
Voted
DBISP2P
2003
Springer
152views Database» more  DBISP2P 2003»
15 years 2 months ago
An Adaptive and Scalable Middleware for Distributed Indexing of Data Streams
Abstract. We are witnessing a dramatic increase in the use of datacentric distributed systems such as global grid infrastructures, sensor networks, network monitoring, and various ...
Ahmet Bulut, Roman Vitenberg, Fatih Emekçi,...
SAC
2005
ACM
15 years 3 months ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
14 years 7 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim