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DATAMINE
2002
53views more  DATAMINE 2002»
13 years 4 months ago
On Issues of Instance Selection
Huan Liu, Hiroshi Motoda
CVPR
2009
IEEE
14 years 12 months ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...
INFOCOM
2003
IEEE
13 years 10 months ago
Load Balancing and Stability Issues in Algorithms for Service Composition
— Service composition enables flexible creation of new services by assembling independent service components. We are focused on the scenario where such composition takes place a...
Bhaskaran Raman, Randy H. Katz
PAMI
2006
206views more  PAMI 2006»
13 years 4 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
DATAMINE
2002
169views more  DATAMINE 2002»
13 years 4 months ago
Advances in Instance Selection for Instance-Based Learning Algorithms
The basic nearest neighbour classifier suffers from the indiscriminate storage of all presented training instances. With a large database of instances classification response time ...
Henry Brighton, Chris Mellish