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Vladik Kreinovich
University of Texas at El Paso
El Paso, Texas
 

Vladik Kreinovich received his MS in Mathematics and Computer Science from St. Petersburg University, Russia, in 1974, and PhD from the Institute of Mathematics, Soviet Academy of Sciences, Novosibirsk, in 1979. From 1975 to 1980, he worked with the Soviet Academy of Sciences; during this time, he worked with the Special Astrophysical Observatory (focusing on the representation and processing of uncertainty in radioastronomy). For most of the 1980s, he worked on error estimation and intelligent information processing for the National Institute for Electrical Measuring Instruments, Russia. In 1989, he was a visiting scholar at Stanford University. Since 1990, he has worked in the Department of Computer Science at the University of Texas at El Paso. In addition, he has served as an invited professor in Paris (University of Paris VI), France; Hong Kong; St. Petersburg, Russia; and Brazil.

 

His main research interests are the representation and processing of uncertainty, especially interval computations and intelligent control. He has written three books, edited six books, and written more than 800 papers. Vladik is a member of the editorial board of the international journal Reliable Computing (formerly Interval Computations) and several other journals. In addition, he is the co-maintainer of the international Web site on interval computations (http://www.cs.utep.edu/interval-comp).

 

Vladik serves as president of the North American Fuzzy Information Processing Society; is a foreign member of the Russian Academy of Metrological Sciences; was the recipient of the 2003 El Paso Energy Foundation Faculty Achievement Award for Research awarded by the University of Texas at El Paso; and was a co-recipient of the 2005 Star Award from the University of Texas System.


     

 Exact algorithms via monotone local search
Fomin F., Gaspers S., Lokshtanov D., Saurabh S.  Journal of the ACM 66(2): 1-23, 2019. Type: Article

Many important problems are NP-complete; this means that, unless P = NP, we cannot have a polynomial-time (feasible) algorithm for solving all instances of this problem. For each such problem, there is an exhaustive search algorithm that requires ...

 

Explaining explanations in AI
Mittelstadt B., Russell C., Wachter S.  FAT* 2019 (Proceedings of the Conference on Fairness, Accountability, and Transparency, Atlanta, GA,  Jan 29-31, 2019) 279-288, 2019. Type: Proceedings

Everyone agrees that artificial intelligence (AI) should be explainable; there is even an abbreviation for this: xAI. But opinions differ on what it means. This paper is a survey of different approaches to xAI....

 

Is the stack distance between test case and method correlated with test effectiveness?
Niedermayr R., Wagner S.  EASE 2019 (Proceedings of the Evaluation and Assessment on Software Engineering, Copenhagen, Denmark,  Apr 15-17, 2019) 189-198, 2019. Type: Proceedings

In general, it is not algorithmically possible to always prove a program’s correctness or incorrectness. So, in practice, a program’s correctness is usually judged by testing the program on test cases from some test suite. How can we g...

 

Credulous acceptability, poison games and modal logic
Grossi D., Rey S.  AAMAS 2019 (Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, Montreal, QC, Canada,  May 13-17, 2019) 1994-1996, 2019. Type: Proceedings

Abstract argumentation theory is based on the notion that argument x attacks argument y. A set of arguments S is “admissible” if no arguments within the set attack each other, an...

 

Computing the homology of basic semialgebraic sets in weak exponential time
Bürgisser P., Cucker F., Lairez P.  Journal of the ACM 66(1): 1-30, 2019. Type: Article

A semialgebraic set is a subset of a finite-dimensional Euclidean space defined by a finite list of polynomial equalities and inequalities. These sets can be weird, so it desirable to be able to describe their topological shape, in particular, to ...

 
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