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Leslie G. Valiant

Leslie G. Valiant

D-Index & Metrics

Computer Science

D-Index
66
Citations
46322
World Ranking
2248
National Ranking
1120

Mathematics

D-Index
57
Citations
35424
World Ranking
661
National Ranking
330

Research.com Recognitions

  • 2019 - Member of Academia Europaea
  • 2012 - ACM Fellow For transformative contributions to the theory of computation.
  • 2010 - A. M. Turing Award 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.
  • 2008 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2001 - Member of the National Academy of Sciences
  • 1992 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For the development of computational learning theory, and providing a scientific basis for research in machine learning.
  • 1991 - Fellow of the Royal Society, United Kingdom
  • 1986 - Rolf Nevanlinna Prize "Valiant has contributed in a decisive way to the growth of almost every branch of the fast growing young tree of theoretical computer science, his theory of counting problems being perhaps his most important and mature work."[9]
  • 1985 - Fellow of John Simon Guggenheim Memorial Foundation
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model
  • Fellow of the International Federation for Information Processing (IFIP) for introducing the concept of the learning machine (theoretical foundation of programming by example) and bulk-synchronous parallel (BSP) model

Overview

Leslie G. Valiant is affiliated with Harvard University in the United States. Their research spans the field of artificial intelligence, with a focus on intelligent tutoring systems and adaptive learning.

Recent papers authored by Leslie G. Valiant include:

  • How to Augment Learning with Reasoning?, 2021, IEEE/WIC/ACM International Conference on Web Intelligence
  • Index, 2024, Princeton University Press eBooks

Publication venues frequently featuring Valiant's work are:

  • IEEE/WIC/ACM International Conference on Web Intelligence
  • Princeton University Press eBooks

The scientist has also published books with Princeton University Press. One notable book is The Importance of Being Educable, published in 2024.

Valiant's research topics concentrate on intelligent tutoring systems and adaptive learning.

  • Intelligent Tutoring Systems and Adaptive Learning

Throughout their career, Leslie G. Valiant has received multiple awards and honors, including:

  • Member of Academia Europaea (2019)
  • ACM Fellow (2012), for transformative contributions to the theory of computation
  • A. M. Turing Award (2010), 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
  • Fellow of the American Association for the Advancement of Science (AAAS) (2008)
  • Member of the National Academy of Sciences (2001)
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) (1992), for the development of computational learning theory and providing a scientific basis for research in machine learning
  • Fellow of the Royal Society, United Kingdom (1991)
  • Rolf Nevanlinna Prize (1986), recognized for contributions to theoretical computer science, especially the theory of counting problems
  • Fellow of John Simon Guggenheim Memorial Foundation (1985)
  • Fellow of the International Federation for Information Processing (IFIP), for introducing the concept of the learning machine and the bulk-synchronous parallel (BSP) model

Best Publications

  • A theory of the learnable

    L. G. Valiant

  • A bridging model for parallel computation

    Leslie G. Valiant

  • The complexity of computing the permanent

    Leslie G. Valiant

  • A theory of the learnable

    Unknown

  • THE COMPLEXITY OF ENUMERATION AND RELIABILITY PROBLEMS

    Leslie G. Valiant

  • NP is as easy as detecting unique solutions

    L. G. Valiant;V. V. Vazirani

  • Cryptographic limitations on learning Boolean formulae and finite automata

    Michael Kearns;Leslie Valiant

  • Random generation of combinatorial structures from a uniform distribution

    Mark R. Jerrum;Leslie G. Valiant;Vijay V. Vazirani

  • Fast probabilistic algorithms for hamiltonian circuits and matchings

    Dana Angluin;Leslie G. Valiant

  • Universal schemes for parallel communication

    L. G. Valiant;G. J. Brebner

  • A SCHEME FOR FAST PARALLEL COMMUNICATION

    Leslie G. Valiant

  • General purpose parallel architectures

    L. G. Valiant

  • Computational limitations on learning from examples

    Leonard Pitt;Leslie G. Valiant

  • A general lower bound on the number of examples needed for learning

    Andrzej Ehrenfeucht;David Haussler

  • Completeness classes in algebra

    L. G. Valiant

  • Evolvability

    Unknown

  • Parallelism in Comparison Problems

    Leslie G. Valiant

  • Universality considerations in VLSI circuits

    L. G. Valiant

  • Learning disjunction of conjunctions

    L. G. Valiant

  • Quantum Circuits That Can Be Simulated Classically in Polynomial Time

    Leslie G. Valiant

  • General context-free recognition in less than cubic time

    Leslie G. Valiant

  • Random generation of combinatorial structures from a uniform

    M R Jerrum;L G Valiant;V V Vazirani

Frequent Co-Authors

Michael Kearns
Michael Kearns University of Pennsylvania
Leonard Pitt
Leonard Pitt University of Illinois at Urbana-Champaign
Vitaly Feldman
Vitaly Feldman Apple (United States)
Vijay V. Vazirani
Vijay V. Vazirani University of California, Irvine
Mike Paterson
Mike Paterson University of Warwick
John H. Reif
John H. Reif Duke University
Nicholas Pippenger
Nicholas Pippenger Harvey Mudd College
John E. Hopcroft
John E. Hopcroft Cornell University
Pinyan Lu
Pinyan Lu Shanghai University of Finance and Economics
Dana Angluin
Dana Angluin Yale University

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