Leslie Valiant biography




 Leslie Valiant, in full Leslie Gabriel Valiant, (born March 28, 1949, Budapest, Hung.), Hungarian-born American laptop scientist and winner of the 2010 A.M. Turing Award, the best honour in laptop science, “for his fundamental contributions to the development of computational learning theory and to the broader theory of computer science.”

Valiant obtained a bachelor’s diploma in arithmetic from the University of Cambridge in 1970 and a diploma in laptop science from Imperial College, London, in 1973. He was an assistant professor at Carnegie Mellon University in Pittsburgh from 1973 to 1974, and he obtained a doctorate in laptop science from the University of Warwick in Coventry, Eng., in 1974. He grew to become a lecturer on the University of Leeds and later on the University of Edinburgh. In 1982 he grew to become a professor of laptop science and utilized arithmetic at Harvard University. He was awarded the Rolf Nevanlinna Prize, which is given for work coping with the mathematical elements of info science, on the International Congress of Mathematicians in Berkeley, Calif., in 1986.

Valiant’s most-notable paper, “A Theory of the Learnable” (1984), supplied a mathematical basis for describing how a pc may study. In this paper Valiant launched the “probably approximately correct” (PAC) mannequin, during which an algorithm posits a speculation primarily based on some knowledge set and applies that speculation to future knowledge. The speculation will possible have some degree of error, and the PAC mannequin provides a framework for figuring out that degree and thus how effectively the algorithm can study. The PAC mannequin has been drastically influential in synthetic intelligence and in purposes similar to handwriting recognition and filtering undesirable e-mails.

Valiant made key contributions to the speculation of computational complexity. In 1979 he created a brand new class of complexity, #P, during which a #P drawback is figuring out the variety of options to an NP drawback. He found the sudden outcome that although it may be very simple to find out whether or not sure issues have an answer, it may be extraordinarily exhausting to find out the variety of options.

Valiant additionally wrote a number of papers concerning the principle of parallel computing, during which an issue is damaged down into a number of components which are labored on concurrently by a number of processors. In “A Bridging Model for Parallel Computation” (1990), he launched the majority synchronous parallel (BSP) mannequin, during which particular person processors talk with one another solely after ending their computations. Each cycle of computation, communication, after which synchronization of the processors is named a superstep. Separating computation from communication avoids cases of impasse, during which exercise stops as a result of every processor is ready for knowledge from one other processor.

Valiant has utilized strategies from laptop science and arithmetic to understanding the human mind. In his guide Circuits of the Mind (1994), he posited a “neuroidal” mannequin that may clarify how the mind can study and carry out sure duties sooner than an digital laptop although the person neurons are comparatively gradual and sparsely related to one another.

 

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