Leslie Valiant

Leslie Gabriel Valiant

Valiant was educated at King's College, Cambridge,^[14][6] Imperial College London,^[14][6] and the University of Warwick where he received a PhD in computer science in 1974.^[15][1]

Research and career

Valiant is world-renowned for his work in

Valiant's 2013 book is Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World.^[20] In it he argues, among other things, that evolutionary biology does not explain the rate at which evolution occurs, writing, for example, "The evidence for Darwin's general schema for evolution being essentially correct is convincing to the great majority of biologists. This author has been to enough natural history museums to be convinced himself. All this, however, does not mean the current theory of evolution is adequately explanatory. At present the theory of evolution can offer no account of the rate at which evolution progresses to develop complex mechanisms or to maintain them in changing environments."

Valiant started teaching at

Leslie Valiant has contributed in a decisive way to the growth of theoretical computer science. His work is concerned mainly with quantifying mathematically the resource costs of solving problems on a computer. In early work (1975), he found the asymptotically fastest algorithm known for recognising context-free languages. At the same time, he pioneered the use of communication properties of graphs for analysing computations. In 1977, he defined the notion of ‘sharp-P’ (#P)-completeness and established its utility in classifying counting or enumeration problems according to computational tractability. The first application was to counting matchings (the matrix permanent function). In 1984, Leslie introduced a definition of inductive learning that, for the first time, reconciles computational feasibility with the applicability to nontrivial classes of logical rules to be learned. This notion, later called ‘probably approximately correct learning’, became a theoretical basis for the development of machine learning. In 1989, he formulated the concept of bulk synchronous computation as a unifying principle for parallel computation. Leslie received the Nevanlinna Prize in 1986, and the Turing Award in 2010.[26]

The citation for his A.M. Turing Award reads:

For transformative contributions to the theory of computation, including the theory of probably approximately correct (PAC) learning, the complexity of enumeration and of algebraic computation, and the theory of parallel and distributed computing.^[6]

Personal life

His two sons Gregory Valiant^[27] and Paul Valiant^[28] are both also theoretical computer scientists.^[8]

References