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IDA
2002
Springer
13 years 6 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
SAINT
2005
IEEE
14 years 9 days ago
Inductive Logic Programming for Structure-Activity Relationship Studies on Large Scale Data
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
ICTAI
2006
IEEE
14 years 22 days ago
On the Relationships between Clustering and Spatial Co-location Pattern Mining
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include servi...
Yan Huang, Pusheng Zhang
ICRA
2010
IEEE
154views Robotics» more  ICRA 2010»
13 years 5 months ago
Activation of a mobile robot through a brain computer interface
- This work presents the development of a brain computer interface as an alternative communication channel to be used in Robotics. It encompasses the implementation of an electroen...
Alexandre Ormiga Galvão Barbosa, David Rona...
BMCBI
2008
138views more  BMCBI 2008»
13 years 6 months ago
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote ho
Background: Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features. This uniqu...
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup...