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 ...




Xplore Articles related to Unsupervised learning

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Real-time pose classification for driver monitoring

Xia Liu; Youding Zhu; Fujimura, K. Intelligent Transportation Systems, 2002. Proceedings. The IEEE 5th International Conference on, 2002

Driver pose estimation is one of the key components for future driver assistance systems since driver pose contains much information about his driving condition such as attention and fatigue levels. To this goal, a system is presented that detects the pose of the driver face in real time under realistic lighting conditions. The goal of the work is to automate ...


A new technique for the classification and decomposition of EMG signals

Christodoulou, C.I.; Pattichis, C.S. Neural Networks, 1995. Proceedings., IEEE International Conference on, 1995

The shapes and firing rates of motor unit action potentials (MUAPs) in an electromyographic (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this information from EMG signals recorded at force levels up to 20% of maximum voluntary contraction (MVC) it is required: (i) To identify the MUAPs composing the EMG ...


Incorporating unsupervised learning with self-organizing map for visualizing mixed data

Chung-Chain Hsu; Chien-Hao Kung Natural Computation (ICNC), 2013 Ninth International Conference on, 2013

In previous studies, a modified SOM extended with distance hierarchies has been proposed to alleviate handling of categorical values. The model was able to take into account the semantics embedded in categorical values. However, the proposed approach required the presence of a class attribute or domain experts. In this article, we propose a model incorporating unsupervised learning of distance hierarchies ...


A proposal of CMAC with foresight knowledge layer for heterogeneous multi-agent system

Hoshino, Y.; Sakakura, A.; Kamei, K. Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on, 2004

The purpose of our research is the acquisition of cooperative behaviors in a heterogeneous multi-agent system. In this paper, we used the fire panic problem and we have tried to be learned how agents escape from the fire. Also, we have observed agents behavior and checked a character of agent types. In the fire panic problem, a fire exists in ...


Modular Fuzzy Neural Networks for Imitative Learning of A Partner Robot

Kubota, N.; Shimizu, T. Neural Networks, 2006. IJCNN '06. International Joint Conference on, 2006

Imitation is a powerful tool for behavior learning and human communication. Basically, imitative learning is composed of model observation and model reproduction. This paper applies a spiking neural network and self-organizing map for model observation, and modular fuzzy neural networks and a steady- state genetic algorithm for model reproduction. The proposed method is applied for a partner robot interacting with ...


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