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Recent advances on machine learning and Cybernetics
2010
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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We would like to thank the Editor-in-Chief of SOFT COM-PUTING for the encouragement, support and guidance during the realization of this special issue.
Guest Editors ...
The Guest Editors issue would like to take this opportunity and express their sincere thanks to the reviewers for their detailed comments as well as constructive suggestions on how to improve the quality ...
Several contributions elaborate on realworld applications of machine learning and cybernetics to medical image processing and business intelligence. ...
doi:10.1007/s00500-010-0590-2
fatcat:swmdjebi7nhrrfzwg6bl3obb4u
International journal of machine learning and cybernetics
2010
International Journal of Machine Learning and Cybernetics
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The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid ...
New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC. ...
doi:10.1007/s13042-010-0010-z
fatcat:voofi5zkljgbte4d5mnng4zd2e
A machine learning approach to recognizing acronyms and their expansion
2005
2005 International Conference on Machine Learning and Cybernetics
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The study presents a simplified feature extraction process from spatial and temporal traits of the event feeds that is further subjected to the machine learning mechanism for boosting recognition performance ...
With the wide ranges of real-time event feed capturing devices, there has been significant progress in the area of digital image processing towards activity detection and recognition. ...
There are various justifications of using machine-based learning approach. ...
doi:10.1109/icmlc.2005.1527330
fatcat:fglaeyg7u5g2folx75xfbi6ldu
Program Committee
2020
2020 International Conference on Machine Learning and Cybernetics (ICMLC)
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International Conference on Machine Learning and Cybernetics (ICMLC) | 978-1-6654-1943-7/20/$31.00 ©2020 IEEE | DOI: 10.1109/ICMLC51923.2020.9469555 ...
doi:10.1109/icmlc51923.2020.9469555
fatcat:jzbcbhx5ibg73jdcegxnkk26aa
Parallel classifiers ensemble with hierarchical machine learning for imbalanced classes
2008
2008 International Conference on Machine Learning and Cybernetics
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Experimental results in machine vision quality inspection showed that the approach could effectively improve classification speed and decrease total risk for imbalanced classes' classification. ...
Most samples would be correctly recognized by the first classifier, and the second relatively slower classifier could be ended. The second one was only trained and worked for less difficult samples. ...
So some practicable indexes must be transformed from expression (1) for machine learning and evaluation. ...
doi:10.1109/icmlc.2008.4620385
fatcat:2al56wnq4jby5ckr3xz3j7s3k4
Contrast Learning for Conceptual Proximity Matching
2007
2007 International Conference on Machine Learning and Cybernetics
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The approach is based on the idea that processing example cases that contrast with existing knowledge but are conceptually close provide a learning opportunity. ...
We present experimental results with a set of real life examples and demonstrate that the newly acquired knowledge facilitates processing of novel cases. ...
This is a common sense rule that was learned from the contrast between terms live and move present respectively in the KB and in an example case. ...
doi:10.1109/icmlc.2007.4370853
fatcat:n7kggqqxfrbcjfbinjiuyzhq6m
Editorial
2015
International Journal of Machine Learning and Cybernetics
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The adoption of Machine Learning (ML) and/or Computational Intelligence (CI) in handling big data could offer a number of advantages. ...
Drifts are detected by comparing two accuracies: (i) the accuracy of an ensemble on the recent examples, and (ii) the accuracy from the beginning of the learning process. ...
The adoption of Machine Learning (ML) and/or Computational Intelligence (CI) in handling big data could offer a number of advantages. ...
doi:10.1007/s13042-015-0429-3
fatcat:6ml6qxnwxvb33mbdvpu67rooey
List of Reviewers
2020
2020 International Conference on Machine Learning and Cybernetics (ICMLC)
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International Conference on Machine Learning and Cybernetics (ICMLC) | 978-1-6654-1943-7/20/$31.00 ©2020 IEEE | DOI: 10.1109/ICMLC51923.2020.9469559 ...
doi:10.1109/icmlc51923.2020.9469559
fatcat:l4zfp4xqjjbztc2o4avdrnewfi
Applying machine learning techniques in detecting Bacterial Vaginosis
2014
2014 International Conference on Machine Learning and Cybernetics
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We isolated the clinical and medical features from the full set of raw data, we compared the accuracy, precision, recall and F-measure and time elapsed for each feature selection and classification grouping ...
This paper seeks to uncover the most important features for diagnosis and in turn employ classification algorithms on those features. ...
The author would like to thank the NSF, BEACON and NIH for their support of this research. ...
doi:10.1109/icmlc.2014.7009123
pmid:25914861
pmcid:PMC4407517
dblp:conf/icmlc/BakerAFBD14
fatcat:hwceyh4ah5a6pnchpsxpmsddtm
Incremental extreme learning machine based on deep feature embedded
2015
International Journal of Machine Learning and Cybernetics
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To solve the problems above, we summarize the features of extreme learning machine and deep belief networks, and then propose Incremental extreme learning machine based on Deep Feature Embedded algorithm ...
Extreme learning machine (ELM) algorithm is used to train Single-hidden Layer Feed forward Neural Networks. And Deep Belief Network (DBN) is based on Restricted Boltzmann Machine (RBM). ...
extreme learning machine [9] . ...
doi:10.1007/s13042-015-0419-5
fatcat:pl445zsspvf2bepxezvxza352y
Learning ontology from relational database
2005
2005 International Conference on Machine Learning and Cybernetics
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However, building ontology by hand is a very hard and error-prone task. Learning ontology from existing resources is a good solution. ...
Because relational database is widely used for storing data and OWL is the latest standard recommended by W3C, this paper proposes an approach of learning OWL ontology from data in relational database. ...
Acknowledgements The work was supported by the National Natural Science Foundation of China (Grant No. 60496325) and "211" project. ...
doi:10.1109/icmlc.2005.1527531
fatcat:rj4b32xlmbgetbomjyfjwfu5km
Greetings from General Chairs
2020
2020 International Conference on Machine Learning and Cybernetics (ICMLC)
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Peng Shi and Cheng-Chew Lim General Chairs, ICMLC International Conference on Machine Learning and Cybernetics (ICMLC) | 978-1-6654-1943-7/20/$31.00 ©2020 IEEE | DOI: 10.1109/ICMLC51923.2020.9469552 ...
Virtual conferences at ICMLC will also show state-of-the-art technologies, ideas, and solutions. ...
doi:10.1109/icmlc51923.2020.9469552
fatcat:4pqx36mqordnfcntm2aknpyolm
Clustering ensemble method
2018
International Journal of Machine Learning and Cybernetics
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It employs two similarity measures, cluster similarity and a newly defined membership similarity, and works adaptively through three stages. ...
Our proposed method is tested on various real-world benchmark datasets and its performance is compared with other state-of-the-art clustering ensemble methods, including the Co-association method and the ...
Introduction In the context of machine learning, an ensemble is generally defined as "a machine learning system that is constructed with a set of individual models working in parallel, whose outputs are ...
doi:10.1007/s13042-017-0756-7
fatcat:meaa6qmp3nfa7honl5pdyoa27e
Applications for Machine Learning [Editorial]
2021
IEEE Systems Man and Cybernetics Magazine
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In this issue of IEEE Systems, Man, and Cybernetics Magazine, we present four articles related to the fascinating topic of machine learning and its application for real-world systems. ...
It is argued that novel machine learning techniques have excellent accuracy but poor explainability and interpretability. ...
doi:10.1109/msmc.2021.3058718
fatcat:5tcc264mgvcn3l6qioup2ba65a
Gained Knowledge Exchange and Analysis for Meta-Learning
2007
2007 International Conference on Machine Learning and Cybernetics
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learning processes and their results. ...
Efficient meta-learning is possible only within a versatile and flexible data mining framework providing uniform procedures for dealing with different kinds of methods and tools for thorough analysis of ...
, the term learning machine (learning method, shortly machine) is used to describe an adaptive algorithm. ...
doi:10.1109/icmlc.2007.4370251
fatcat:2drg4bxrgfbrxopnw7qm77buje
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