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» Improving spatial locality of programs via data mining
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TMI
2002
248views more  TMI 2002»
13 years 4 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson
ASPLOS
1994
ACM
13 years 9 months ago
Compiler Optimizations for Improving Data Locality
In the past decade, processor speed has become significantly faster than memory speed. Small, fast cache memories are designed to overcome this discrepancy, but they are only effe...
Steve Carr, Kathryn S. McKinley, Chau-Wen Tseng
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 8 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
IEEEIAS
2009
IEEE
13 years 12 months ago
Fuzzy Intrusion Detection System via Data Mining Technique with Sequences of System Calls
: There are two main approaches for implementing IDS; Host based and Network based. While the former is implemented in form of software deployed on a host, the latter, usually is b...
Mohammad Akbarpour Sekeh, Mohd. Aizani Bin Maarof
EUROPAR
2001
Springer
13 years 9 months ago
Experiments in Parallel Clustering with DBSCAN
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
Domenica Arlia, Massimo Coppola