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Jose Hernandez-Orallo
Universitat Politecnica de Valencia
Valencia, Spain
 

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.


     

 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...

 

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...

 

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...

 

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...

 

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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