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- Leslie G. Valiant

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
54
Citations
33,257
87
World Ranking
595
National Ranking
310

Computer Science
D-index
62
Citations
39,983
109
World Ranking
1797
National Ranking
978

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

- Artificial intelligence
- Algorithm
- Programming language

Leslie G. Valiant spends much of his time researching Discrete mathematics, Combinatorics, Algebra, Time complexity and Theoretical computer science. His work on Counting problem, Binary logarithm and PP as part of general Discrete mathematics research is often related to Polynomial identity testing, thus linking different fields of science. His research in Combinatorics intersects with topics in Multiprocessing, Complete Boolean algebra and Product term.

Leslie G. Valiant has included themes like Deterministic finite automaton, Quadratic residue, Quantum complexity theory, Graph coloring and True quantified Boolean formula in his Algebra study. His work deals with themes such as Turing machine, Set, Parallelism, Random graph and Parallel algorithm, which intersect with Time complexity. Leslie G. Valiant interconnects Sorting, Model of computation, Complexity class and Boolean circuit in the investigation of issues within Theoretical computer science.

- A theory of the learnable (4315 citations)
- A bridging model for parallel computation (3150 citations)
- The complexity of computing the permanent (2285 citations)

His primary areas of study are Discrete mathematics, Combinatorics, Artificial intelligence, Theoretical computer science and Algorithm. His study in Discrete mathematics is interdisciplinary in nature, drawing from both Computational complexity theory and Algebra. The Concept class and Artificial neural network research he does as part of his general Artificial intelligence study is frequently linked to other disciplines of science, such as Context, therefore creating a link between diverse domains of science.

His Theoretical computer science research integrates issues from Computational learning theory and Boolean function. His Algorithm research is multidisciplinary, incorporating perspectives in Polynomial and Robustness. His Binary logarithm research is multidisciplinary, relying on both Randomized algorithm and Logarithm.

- Discrete mathematics (39.84%)
- Combinatorics (21.09%)
- Artificial intelligence (19.53%)

- Artificial intelligence (19.53%)
- Algorithm (13.28%)
- Cognition (7.03%)

Leslie G. Valiant mainly investigates Artificial intelligence, Algorithm, Cognition, Cortex and Combinatorics. His Artificial intelligence study incorporates themes from Development, Science studies, Cognitive science, Machine learning and Computation. His Computation study combines topics from a wide range of disciplines, such as Computational neuroscience, Random access, Turing and Knowledge acquisition.

His studies in Algorithm integrate themes in fields like Evolutionary algorithm, Polynomial and Stability. His research on Combinatorics frequently links to adjacent areas such as Discrete mathematics. His research investigates the connection between Time complexity and topics such as Planar graph that intersect with issues in Boolean function, Counting problem, Feedback vertex set and Computational complexity theory.

- A bridging model for multi-core computing (137 citations)
- Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (124 citations)
- The Complexity of Symmetric Boolean Parity Holant Problems (22 citations)

- Artificial intelligence
- Algorithm
- Programming language

His primary areas of investigation include Cognition, Algorithm, Combinatorics, Time complexity and Discrete mathematics. In his study, which falls under the umbrella issue of Cognition, Artificial intelligence is strongly linked to Biological neural network. His Artificial intelligence research includes elements of Memorization, Association, Learning theory and Neuroscience.

His work is connected to Computational complexity theory, Boolean function, Counting problem and Vertex cover, as a part of Algorithm. His Homomorphism, Undirected graph and Vertex study, which is part of a larger body of work in Combinatorics, is frequently linked to Constraint satisfaction problem and Subclass, bridging the gap between disciplines. Leslie G. Valiant combines topics linked to Feedback vertex set with his work on Time complexity.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

A theory of the learnable

L. G. Valiant.

symposium on the theory of computing **(1984)**

8377 Citations

A bridging model for parallel computation

Leslie G. Valiant.

Communications of The ACM **(1990)**

5200 Citations

The complexity of computing the permanent

Leslie G. Valiant.

Theoretical Computer Science **(1979)**

3248 Citations

THE COMPLEXITY OF ENUMERATION AND RELIABILITY PROBLEMS

Leslie G. Valiant.

SIAM Journal on Computing **(1979)**

2432 Citations

NP is as easy as detecting unique solutions

L. G. Valiant;V. V. Vazirani.

Theoretical Computer Science **(1986)**

1805 Citations

Cryptographic limitations on learning Boolean formulae and finite automata

Michael Kearns;Leslie Valiant.

Journal of the ACM **(1994)**

1234 Citations

Random generation of combinatorial structures from a uniform distribution

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

Theoretical Computer Science **(1986)**

1118 Citations

Fast probabilistic algorithms for hamiltonian circuits and matchings

Dana Angluin;Leslie G. Valiant.

Journal of Computer and System Sciences **(1979)**

1031 Citations

Universal schemes for parallel communication

L. G. Valiant;G. J. Brebner.

symposium on the theory of computing **(1981)**

888 Citations

A SCHEME FOR FAST PARALLEL COMMUNICATION

Leslie G. Valiant.

SIAM Journal on Computing **(1982)**

843 Citations

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