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» Evaluating algorithms that learn from data streams
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JCB
2007
130views more  JCB 2007»
15 years 4 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
JMLR
2006
186views more  JMLR 2006»
15 years 4 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
ICNC
2005
Springer
15 years 10 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
SSPR
1998
Springer
15 years 8 months ago
Modified Minimum Classification Error Learning and Its Application to Neural Networks
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Hiroshi Shimodaira, Jun Rokui, Mitsuru Nakai
PDPTA
2000
15 years 5 months ago
Evaluation of Neural and Genetic Algorithms for Synthesizing Parallel Storage Schemes
Exploiting compile time knowledge to improve memory bandwidth can produce noticeable improvements at run-time [13, 1]. Allocating the data structure [13] to separate memories when...
Mayez A. Al-Mouhamed, Husam Abu-Haimed