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| Jose Hernandez-Orallo is currently an associate professor in the Department of Information Systems and Computation at the Technical University of Valencia (Spain). He holds a BS and an MS in Computer Science from the Technical University of Valencia, an MS in Engineering from the ¿cole Nationale Sup¿rioure de l'¿lectronique et de ses Applications (France), an MS in Artificial Intelligence, and a Ph.D. in Logic with a doctoral extraordinary prize from the University of Valencia. He has worked for several companies in areas ranging from software development to cryptography in electronic commerce. Since 1996, he has been part of the associate academic staff of the Department of Information Systems and Computation at the Technical University of Valencia, where he has taught courses on software engineering, programming technology, requirement elicitation, software development environments, database systems, and data mining. In 2001, he became an associate professor. His research interests are quite varied, and include several aspects of artificial intelligence and machine learning, software engineering, programming languages, computer networks, and information systems. He has written four books about these topics, as well as several book chapters, journal articles, and conference publications. Presently, he is particularly interested in machine learning, especially data mining and knowledge discovery from databases, inductive (logic) programming and reinforcement learning, decision support systems and classifier evaluation, the application and relationship between ML and software engineering, and the relationship between induction and deduction within the framework of Kolmogorov complexity. In his spare time, Jose is also well known as the best paella cook worldwide. |
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Explainable AI: interpreting, explaining and visualizing deep learning Samek W., Montavon G., Vedaldi A., Hansen L., Muller K., Springer International Publishing, New York, NY, 2019. 452 pp. Type: Book (978-3-030289-53-9)
Deep learning has become so dominant in machine learning, and artificial intelligence (AI) as a whole, that its intrinsic lack of interpretability is paradigmatic for the whole field of explainable AI (XAI). This is why progress in int...
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Jul 24 2020 |
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Deep learning for computer architects Reagen B., Adolf R., Whatmough P., Wei G., Brooks D., Morgan & Claypool Publishers, San Rafael, CA, 2017. 124 pp. Type: Book (978-1-627057-28-8)
I was looking for a book on deep learning that could put the emphasis on efficiency, rather than achieving task accuracy at whatever cost. Although this book was not meant for this purpose, it changed my perception completely. It is an...
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Jan 31 2018 |
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Learning adaptive dressing assistance from human demonstration Pignat E., Calinon S. Robotics and Autonomous Systems 93 61-75, 2017. Type: Article
Is dressing a daily chore, in a range that includes cooking, cleaning, and eating, whose automation might have an enormous impact, especially because of aging? This is unclear, but nevertheless the progress in this task may be extrapol...
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Aug 16 2017 |
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Cognitive infocommunications (CogInfoCom) Baranyi P., Csapo A., Sallai G., Springer International Publishing, New York, NY, 2015. 219 pp. Type: Book (978-3-319196-07-7)
There is general agreement that devices (including computers, robots, and other gadgets) and their interconnection will be increasingly more adaptive and--despite the overuse of the term--“intelligent....
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Sep 15 2016 |
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Inducing semantic relations from conceptual spaces Derrac J., Schockaert S. Artificial Intelligence 228(C): 66-94, 2015. Type: Article
Artificial intelligence is experiencing a new golden age with the use of powerful machine learning tools that are able to process massive amounts of data. However, many of these tools produce systems that are seen as a jumble of weight...
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Dec 22 2015 |
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Towards UCI+: a mindful repository design Macià N., Bernadó-Mansilla E. Information Sciences 261237-262, 2014. Type: Article
The evaluation of machine learning algorithms has always been controversial. What datasets, experimental setting, and statistical tests must be chosen? Dataset repositories such as UCI have been enormously handy for machine learning re...
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Sep 12 2014 |
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Big data computing Akerkar R., Chapman & Hall/CRC, Boca Raton, FL, 2014. 564 pp. Type: Book (978-1-466578-37-1), Reviews: (2 of 2)
Whenever a new discipline (or buzzword) appears, we feel the need to understand what it is and how it differs from what existed before. A very explicit declaration about what “big data” means can be found in the pre...
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Jun 6 2014 |
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Believable bots: can computers play like people? Hingston P., Springer Publishing Company, Incorporated, Berlin, Germany, 2012. 328 pp. Type: Book (978-3-642323-22-5)
Despite the funny title, this is not a book about artificial intelligence (AI) in games. Instead, it is about believability in games. With this is mind, the first question that must be addressed is what a believable bot is. The term &a...
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May 22 2013 |
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Comparative experimental studies on spatial memory and learning in rats and robots Barrera A., Cáceres A., Weitzenfeld A., Ramirez-Amaya V. Journal of Intelligent and Robotic Systems 63(3-4): 361-397, 2011. Type: Article
Comparative cognition studies the behavior of different animals, focusing on differences between species. In this paper, the comparison is performed between rats and robots--a novel situation that will surely become more frequ...
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Feb 1 2012 |
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Phase transitions in machine learning Saitta L., Giordana A., Cornujols A., Cambridge University Press, New York, NY, 2011. 410 pp. Type: Book (978-0-521763-91-2)
There has been extensive research in the past three decades about phase transitions and computation--two apparently unrelated areas that come closer when, through statistical tools, physical and computational phenomena are ana...
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Jan 13 2012 |
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