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» A distributed machine learning framework
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MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 5 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
AIIA
2001
Springer
15 years 3 months ago
A New Machine Learning Approach to Fingerprint Classification
We present new fingerprint classification algorithms based on two machine learning approaches: support vector machines (SVMs), and recursive neural networks (RNNs). RNNs are traine...
Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil...
ISNN
2007
Springer
15 years 6 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
ICML
2003
IEEE
16 years 19 days ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
TAICPART
2006
IEEE
134views Education» more  TAICPART 2006»
15 years 5 months ago
Integration Testing of Components Guided by Incremental State Machine Learning
The design of complex systems, e.g., telecom services, is nowadays usually based on the integration of components (COTS), loosely coupled in distributed architectures. When compon...
Keqin Li 0002, Roland Groz, Muzammil Shahbaz