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| Corrado Mencar is currently an assistant professor in the Department of Informatics at the University of Bari (Italy). He received his MS degree in Informatics in 2000 and a PhD in Informatics in 2005, both at the University of Bari. After receiving his master’s degree, he worked as a software analyst and designer for some Italian software firms. In 2005, he joined the University of Bari as an assistant professor, researching computational intelligence and related fields. His current research interests include fuzzy logic and fuzzy systems, granular computing, computational web intelligence, intelligent data analysis and genetic algorithms. The most important achievements in his research are related to the interpretability of fuzzy systems, that is, techniques for endowing fuzzy systems with empirically acquired knowledge that can be communicated to users in a way that is easy to read and understand. He has been involved with several research projects and has written more than 60 peer-reviewed international papers. He also acts as a reviewer for several international journals, is member of the program committees of several conferences, and is an associate editor for the International Journal on Artificial Intelligence. Mencar has taught several undergraduate and graduate courses on topics related to his research, as well as courses on programming fundamentals, computer architectures and operating systems. He supervises of a number of PhD students and is the scientific supervisor of the department library. In addition to his research interests, he is passionate about complex dynamical systems, including biological, social and natural systems. He is an avid reader of books in the field, and is a fan of Richard Dawkins, Douglas Hofstadter and Fritjof Capra. |
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Discrete fuzzy measures: computational aspects Beliakov G., James S., Wu J., Springer International Publishing, New York, NY, 2020. 245 pp. Type: Book (978-3-030153-04-5)
Decision-making is a problem-solving activity aimed at reckoning a choice by taking into account a possibly large number of constraints, preferences, beliefs, and costs, among other things. It is a complex discipline that requires soph...
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Mar 9 2020 |
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The book of why: the new science of cause and effect Pearl J., Mackenzie D., Basic Books, Inc., New York, NY, 2018. 432 pp. Type: Book (978-0-465097-60-9), Reviews: (2 of 2)
In fields such as data science, explainable artificial intelligence (AI), and big data analytics, “why?” is the ultimate question that needs to be answered to make sense of real data. “Why?” has ...
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Aug 2 2019 |
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On the logos: a naïve view on ordinary reasoning and fuzzy logic Trillas E., Springer International Publishing, New York, NY, 2017. 213 pp. Type: Book (978-3-319560-52-6)
There are many books that you read to get answers to questions and doubts, and there are few books that leave you with more questions and doubts than before reading them. Yet, you can still be satisfied with such books because they giv...
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Apr 9 2018 |
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Deep learning neural networks: design and case studies Graupe D., World Scientific Publishing Co, Inc., River Edge, NJ, 2016. 200 pp. Type: Book
Deep learning is a field of study that is gaining much attention both in academia and industry; hence, textbooks and monographs on this subject are increasingly in demand. At first glance, this book by D. Graupe seems well suited for t...
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Apr 26 2017 |
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Low rank approximation: algorithms, implementation, applications Markovsky I., Springer Publishing Company, Incorporated, New York, NY, 2011. 266 pp. Type: Book (978-1-447122-26-5)
Low rank approximation (LRA), a general approach for discovering linear models of data, applies to a wide range of problems in many disciplines, including computer science (CS) and engineering. It is therefore an instructive approach t...
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Dec 5 2012 |
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