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TMI
2010
172views more  TMI 2010»
14 years 8 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
GECCO
2003
Springer
130views Optimization» more  GECCO 2003»
15 years 3 months ago
A New Approach to Improve Particle Swarm Optimization
Abstract. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the methods of selecting inert...
Liping Zhang, Huanjun Yu, Shangxu Hu
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
15 years 1 months ago
Aspects of adaptation in natural and artificial evolution
This work addresses selected aspects of natural evolution, especially of the field of population genetics, that are considered to be meaningful for algorithmic further development...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
15 years 3 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
VLDB
2010
ACM
144views Database» more  VLDB 2010»
14 years 8 months ago
Methods for finding frequent items in data streams
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Graham Cormode, Marios Hadjieleftheriou