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AUSAI
2008
Springer
13 years 10 months ago
Revisiting Multiple-Instance Learning Via Embedded Instance Selection
Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learne...
James R. Foulds, Eibe Frank
FLAIRS
2006
13 years 9 months ago
Focusing Strategies for Multiple Fault Diagnosis
Diagnosing multiple faults for a complex system is often very difficult. It requires not only a model which adequately represents the diagnostic aspect of a complex system, but al...
Tsai-Ching Lu, K. Wojtek Przytula
PAMI
2008
206views more  PAMI 2008»
13 years 8 months ago
Robust Real-Time Unusual Event Detection using Multiple Fixed-Location Monitors
We present a novel algorithm for detection of certain types of unusual events. The algorithm is based on multiple local monitors which collect low-level statistics. Each local moni...
Amit Adam, Ehud Rivlin, Ilan Shimshoni, David Rein...
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 12 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
FSKD
2006
Springer
124views Fuzzy Logic» more  FSKD 2006»
13 years 11 months ago
An Effective Combination of Multiple Classifiers for Toxicity Prediction
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Gongde Guo, Daniel Neagu, Xuming Huang, Yaxin Bi