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ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 6 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
TFS
2008
230views more  TFS 2008»
15 years 6 months ago
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
Abstract--This paper considers the automatic design of fuzzyrule-based classification systems from labeled data. The performance of classifiers and the interpretability of generate...
Eghbal G. Mansoori, Mansoor J. Zolghadri, Seraj D....
JMLR
2007
101views more  JMLR 2007»
15 years 6 months ago
Noise Tolerant Variants of the Perceptron Algorithm
A large number of variants of the Perceptron algorithm have been proposed and partially evaluated in recent work. One type of algorithm aims for noise tolerance by replacing the l...
Roni Khardon, Gabriel Wachman
AEI
1999
120views more  AEI 1999»
15 years 6 months ago
Genetic algorithms for designing multihop lightwave network topologies
Multihop lightwave networks are a means of utilizing the large bandwidth of optical fibers. In these networks, each node has a fixed number of transmitters and receivers connected...
Cenk Gazen, Cem Ersoy
RTS
2002
177views more  RTS 2002»
15 years 6 months ago
Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms
This paper presents a Feedback Control real-time Scheduling (FCS) framework for adaptive realtime systems. An advantage of the FCS framework is its use of feedback control theory ...
Chenyang Lu, John A. Stankovic, Sang Hyuk Son, Gan...