Seminar - Dealing with Uncertainties in Data Processing: from Probabilistic and Interval Uncertainty to Combination of Different Approaches, with Application to Geoinformatics, Bioinformatics, and Engineering

Mason Building, Room 1133
Monday, August 20, 2018 - 13:45


Dr. Vladik Kreinovich
Professor, Computer Science, Border Biomedical Research Center, Cyber-Share, Bioinformatics, and Computational Science
The University of Texas at El Paso

Most data processing techniques traditionally used in scientific and engineering practice are statistical. These techniques are based on the assumption that we know the probability distributions of measurement errors etc. In practice, often, we do not know the distributions, we only know the bound D on the measurement accuracy -- hence, after the get the measurement result X, the only information that we have about the actual (unknown) value x of the measured quantity is that x belongs to the interval [X-D,X+D]. Techniques for data processing under such interval uncertainty are called interval computations; these techniques have been developed since 1950s. There exist a lot of theoretical research and practical applications in dealing with these types of uncertainty: interval, fuzzy, and combined. The purpose of this talk is to describe the theoretical background for interval and combined techniques, to describe the existing practical applications, and ideally, to come up with a roadmap for such techniques. We start with the problem of chip design in computer engineering. In this problem, traditional interval methods lead to estimates with excess width. The reason for this width is that often, in addition to the intervals of possible values of inputs, we also have partial information about the probabilities of different values within these intervals -- and standard interval techniques ignore this information. It is therefore desirable to extend interval techniques to the situations when, in addition to intervals, we also have a partial probabilistic information. In the talk, we give a brief overview of these techniques, and we emphasize the following three application areas: computer engineering, bioinformatics, and geoinformatics.


Dr. 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. His main interests are the representation and processing of uncertainty, especially interval computations and intelligent control. He has published seven books, nineteen edited books, and more than 1,300 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 Vladik is Vice President for Publications of IEEE Systems, Man, and Cybernetics Society, Vice President for Publicity of the International Fuzzy Systems Association (IFSA), and is a foreign member of the Russian Academy of Metrological Sciences.