Unsupervised learning

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In machine learning, unsupervised learning refers to the problem of trying to find hidden structure in unlabeled data. (Wikipedia.org)




IEEE Organizations related to Unsupervised learning

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Conferences related to Unsupervised learning

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2013 International Conference on Machine Learning and Cybernetics (ICMLC)

Statistical Machine Learning, Intelligent & fuzzy control, Pattern Recognition , Ensemble method, Evolutionary computation, Fuzzy & rough set, Data & web mining , Intelligent Business Computing , Biometrics , Bioinformatics , Information retrieval, Cybersecurity, Web intelligence and technology, Semantics & ontology engineering, Social Networks & Ubiquitous Intelligence, Multicriteria decision making, Soft Computing, Intelligent Systems, Speech, Image & Video Processing, Decision Support System

  • 2012 International Conference on Machine Learning and Cybernetics (ICMLC)

    Adaptive systems, Pattern Recognition, Biometrics, Inductive learning, Evolutionary computation, Bioinformatics, Data mining, Information retrieval, Intelligent agent, Financial engineering, Rough Set, Applications.

  • 2011 International Conference on Machine Learning and Cybernetics (ICMLC)

    Adaptive systems, Neural net and support vector machine, Business intelligence, Hybrid and nonlinear system, Biometrics, Fuzzy set theory, fuzzy control and system, Bioinformatics, Knowledge management, Data and web mining, Information retrieval, Intelligent agent, Intelligent and knowledge based system, Financial engineering, Rough and fuzzy rough set, Inductive learning, Networking and information security, Geoinformatics, Evolutionary computation, Pattern Recognition, Ensemble method, Logistics.

  • 2010 International Conference on Machine Learning and Cybernetics (ICMLC)

    Adaptive systems, Neural net and support vector machine, Business intelligence, Hybrid and nonlinear system, Biometrics, Fuzzy set theory, fuzzy control and system, Bioinformatics, Knowledge management, Data and web mining, Information retrieval, Intelligent agent, Intelligent and knowledge based system, Financial engineering, Rough and fuzzy rough set, Inductive learning, Networking and information security, Geoinformatics, Evolutionary computation, Pattern Recognition, Ensemble method, Logistics, Informat

  • 2009 International Conference on Machine Learning and Cybernetics (ICMLC)

    Adaptive systems, Neural net and support vector machine, Business intelligence, Hybrid and nonlinear system, Biometrics, Fuzzy set theory, fuzzy control and system, Bioinformatics, Knowledge management, Data and web mining, Information retrieval, Intelligent agent, Intelligent and knowledge based system, Financial engineering, Rough and fuzzy rough set, Inductive learning, Networking and information security, Geoinformatics, Evolutionary computation, Pattern Recognition, Ensemble method, Logistics, Informat

  • 2008 International Conference on Machine Learning and Cybernetics (ICMLC)

    Adaptive systems, Neural net and support vector machine, Business intelligence, Hybrid and nonlinear system, Biometrics, Fuzzy set theory, fuzzy control and system, Bioinformatics, Knowledge management, Data and web mining, Information retrieval, Intelligent agent, Intelligent and knowledge based system, Financial engineering, Rough and fuzzy rough set, Inductive learning, Networking and information security, Geoinformatics, Evolutionary computation, Pattern Recognition, Ensemble method, Logistics, Informat

  • 2007 International Conference on Machine Learning and Cybernetics (ICMLC)

    Multiple themes included: Generalization Error Model for Pattern Classification, Rough Sets and Fuzzy Rough Sets, Multiple Classifier Systems, Computation Life Science and Bioinformatics, Media Computing, Web Intelligent Computing. Topics included: Adaptive systems, Neural nets and support vector machines, Business intelligence, Hybrid and nonlinear systems, Fuzzy theory, control and systems, Data and web mining, Information retrieval, intelligent agent etc.

  • 2006 International Conference on Machine Learning and Cybernetics (ICMLC)

  • 2005 International Conference on Machine Learning and Cybernetics (ICMLC)


2012 10th World Congress on Intelligent Control and Automation (WCICA 2012)

A. Intelligent Control B. Control Theory and Control Engineering C. Complex Systems and Intelligent Robots D. Others


2012 46th Annual Conference on Information Sciences and Systems (CISS)

Theoretical advances, applications and ideas in the fields of information theory (including application to biological sciences); communication, networking, signal, image and video processing; systems and control; learning and statistical inference.


2012 IEEE 15th International Conference on Computational Science and Engineering (CSE)

The Computational Science and Engineering area has earned prominence through advances in electronic and integrated technologies beginning in the 1940s. Current times are very exciting and the years to come will witness a proliferation in the use of various advanced computing systems. It is increasingly becoming an emerging and promising discipline in shaping future research and development activities in academia and industry, ranging from engineering, science, finance, economics, arts and humanitarian fields, especially when the solution of large and complex problems must cope with tight timing schedules.



Periodicals related to Unsupervised learning

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Knowledge and Data Engineering, IEEE Transactions on

Artificial intelligence techniques, including speech, voice, graphics, images, and documents; knowledge and data engineering tools and techniques; parallel and distributed processing; real-time distributed processing; system architectures, integration, and modeling; database design, modeling, and management; query design, and implementation languages; distributed database control; statistical databases; algorithms for data and knowledge management; performance evaluation of algorithms and systems; data communications aspects; system ...



Most published Xplore authors for Unsupervised learning

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Xplore Articles related to Unsupervised learning

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Generation of sports highlights using a combination of supervised & unsupervised learning in audio domain

Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on, 2003

In our past work we have used supervised audio classification to develop a common audio-based platform for highlight extraction that works across three different sports. We then use a heuristic to post-process the classification results to identify interesting events and also to adjust the summary length. In this paper, we propose a combination of unsupervised and supervised learning approaches to ...


Unsupervised and active learning in automatic speech recognition for call classification

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on, 2004

A key challenge in rapidly building spoken natural language dialog applications is minimizing the manual effort required in transcribing and labeling speech data. This task is not only expensive but also time consuming. We present a novel approach that aims at reducing the amount of manually transcribed in-domain data required for building automatic speech recognition (ASR) models in spoken language ...


Self-organising fuzzy perceptrons applied to power system stability

Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American, 1997

Organising and adjusting a neuro-fuzzy system is been presented in this paper. A fuzzy inference system has been implemented on a multilayer perceptron, in which the weights are fuzzy membership. The parameters of the fuzzy multilayer perceptron are meaningful and have physical interpretation. A hierarchical procedure is proposed for design and organising the system in three levels: predefining the rules, ...


Towards a knowledge based system for the clinical evaluation of the electroencephalogram and visual evoked potentials

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on, 1998

The objective of our research is to develop computer based tools to automate the clinical evaluation of the electroencephalogram (EEG) and visual evoked potentials (VEP). The paper describes a set of solutions to support all the aspects regarding the standard procedures of the diagnosis in neurophysiology. More specifically, the paper focuses on the description of an approach to automate the ...


Clustering Ensemble for Unsupervised Feature Selection

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on, 2009

A new feature selection algorithm for unsupervised learning is proposed. It is based on the assumption that, in absence of class labels, the clustering ensemble result can be employed as a heuristic to guide the feature selection. Therefore, a modified RReliefF algorithm is then used to assign the rankings for every feature. The main advantage of the proposed unsupervised feature ...


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Educational Resources on Unsupervised learning

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eLearning

Improved random walker algorithm for image segmentation

Yusuf Artan; Imam Samil Yetik Image Analysis & Interpretation (SSIAI), 2010 IEEE Southwest Symposium on, 2010

General purpose image segmentation is one of the important and challenging problems in image processing. Objective of image segmentation is to group regions with coherent cues such as intensity, texture, color and shape together. Most of the earlier studies on this issue are based on supervised and unsupervised learning methods. In this paper, we develop a semi-supervised image segmentation technique ...


Self-organization neural network for multiple texture image segmentation

Woobeom Lee; Wookhyun Kim TENCON 99. Proceedings of the IEEE Region 10 Conference, 1999

Texture analysis is an important technique in many image processing areas, such as scene segmentation, object recognition, and shape and depth perception. But no efficient methods captures all aspects of the very diverse texture family including natural scenes. We propose a novel approach for efficient texture image analysis that use unsupervised learning schemes for the texture recognition task. The self-organization ...


Neural networks

J. Staley Neural Networks, 1999. IJCNN '99. International Joint Conference on, 1999

A history of the development of neural nets is given. Types of learning are discussed. Applications are listed, with brief comments on nets' suitability to a few of them


Notice of Retraction<BR>Application of weighted distance in clustering of hydraulic press

Wang Ya; Li Da-hua; Zhang Si-bing Computer Engineering and Technology (ICCET), 2010 2nd International Conference on, 2010

Notice of Retraction After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper. The presenting author of this paper ...


Myoelectric signal classification using evolutionary hybrid RBF-MLP networks

A. M. S. Zalzala; N. Chaiyaratana Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 2000

This paper introduces a hybrid neural structure using radial-basis functions (RBF) and multilayer perceptron (MLP) networks. The hybrid network is composed of one RBF network and a number of MLPs, and is trained using a combined genetic/unsupervised/supervised learning algorithm. The genetic and unsupervised learning algorithms are used to locate the centres of the RBF part in the hybrid network. In ...


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