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» Learning Switching Concepts
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131
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MCS
2009
Springer
15 years 8 months ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar
SIAMCOMP
1998
86views more  SIAMCOMP 1998»
15 years 3 months ago
Exact Learning of Discretized Geometric Concepts
We first present an algorithm that uses membership and equivalence queries to exactly identify a discretized geometric concept defined by the union of m axis-parallel boxes in d-...
Nader H. Bshouty, Paul W. Goldberg, Sally A. Goldm...
118
Voted
MLDM
2001
Springer
15 years 8 months ago
Concepts Learning with Fuzzy Clustering and Relevance Feedback
Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications . . . . . . . . . . . . . . . . . 23 R. Schmidt and L. Gierl Are Case-Based Reasoning and...
Bir Bhanu, Anlei Dong
143
Voted
PCM
2005
Springer
107views Multimedia» more  PCM 2005»
15 years 9 months ago
Salient Feature Selection for Visual Concept Learning
Abstract. Image classification could be treated as an effective solution to enable keyword-based semantic image retrieval. In this paper, we propose a novel image classification...
Feng Xu, Lei Zhang, Yu-Jin Zhang, Wei-Ying Ma
137
Voted
ICIP
2008
IEEE
16 years 5 months ago
Cross-domain learning methods for high-level visual concept classification
Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...