This work explores current applications of robust optimization in data mining, offering an overview of this rapidly growing field and presenting machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems.
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“The goal of the book is to provide a guide for junior researchers interested in pursuing theoretical research in data mining and robust optimization and has been developed so that each chapter can be studied independent of the others.” (Hans Benker, Zentralblatt MATH, Vol. 1260, 2013)Dr. Panos M. Pardalos is Distinguished Professor of Industrial and Systems Engineering at the University of Florida. He is also affiliated faculty member of the Computer Science Department, the Hellenic Studies Center, and the Biomedical Engineering Program. He is also the director of the Center for Applied Optimization. Dr. Pardalos obtained a PhD degree from the University of Minnesota in Computer and Information Sciences. He has held visiting appointments at Princeton University, DIMACS Center, Institute of Mathematics and Applications, FIELDS Institute, AT&T Labs Research, Trier University, Linkoping Institute of Technology, and Universities in Greece. He has received numerous awards including, University of Florida Research Foundation Professor, UF Doctoral Dissertation Advisor/Mentoring Award, Foreign Member of the Royal Academy of Doctors (Spain), Foreign Member Lithuanian Academy of Sciences, Foreign Member of the Ukrainian Academy of Sciences, Foreign Member of the Petrovskaya Academy of Sciences and Arts (Russia), and Honorary Member of the Mongolian Academy of Sciences. Dr. Pardalos received the degrees of Honorary Doctor from Lobachevski University (Russia) and the V.M. Glushkov Institute of Cybernetics (Ukraine), he is a fellow of AAAS, a fellow of INFORMS, and in 2001 he was awarded the Greek National Award and Gold Medal for Operations Research. Dr. Theodore B. Trafalis is a Professor in the School of Industrial Engineering at the University of Oklahoma. He earned his BS in mathematics from the University of Athens, Greece, his MS in Applied Mathematics, MSIE, and PhD in Operations Research from Purdue University. He is a member of ORSA, SIAM, Hellenic Operational Society, International Society of Multiple criteria Decision Making, and the International Society of Neural Networks. His is listed in the 1993/1994 edition of Who's Who in the World. He was a visiting Assistant Professor at Purdue Univer
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. This brief will appeal to theoreticians and data miners working in this field. 72 pp. Englisch. Codice articolo 9781441998774
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Taschenbuch. Condizione: Neu. Neuware -Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field ofrobust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems.Thisbrief will appeal to theoreticians and data miners working in this field.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 72 pp. Englisch. Codice articolo 9781441998774
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