# Leslie Valiant

> computer scientist, university teacher (1949-)

**Wikidata**: [Q93154](https://www.wikidata.org/wiki/Q93154)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Leslie_Valiant)  
**Source**: https://4ort.xyz/entity/leslie-valiant

## Summary
Leslie Valiant is a British-American computer scientist and university teacher known for his foundational contributions to computational learning theory and complexity theory. He was awarded the 2010 Turing Award for his transformative work in the field of computer science.

## Biography
- Born: March 28, 1949, in Budapest
- Nationality: United Kingdom, United States
- Education: Ph.D. from University of Warwick (1974), B.A. from Imperial College London
- Known for: Computational learning theory, complexity theory, PAC learning
- Employer(s): Harvard University (since 1982), University of Edinburgh (1976-1982), University of Leeds (1974-1976), Carnegie Mellon University (1973-1974)
- Field(s): Computer science, theoretical computer science

## Contributions
Leslie Valiant is best known for developing the Probably Approximately Correct (PAC) learning model, which provides a mathematical framework for understanding machine learning. His work established computational learning theory as a rigorous field, defining what it means for a learning algorithm to be effective. Valiant also made fundamental contributions to parallel computing, including the development of the complexity class NC and the introduction of the bulk synchronous parallel model. His 1979 paper "The Complexity of Computing the Permanent" proved that computing the permanent of a matrix is #P-complete, a landmark result in computational complexity. These contributions have shaped both theoretical computer science and practical machine learning approaches used today.

## FAQs
### Q: What is Leslie Valiant most famous for?
A: Leslie Valiant is most famous for developing the Probably Approximately Correct (PAC) learning model, which provides a mathematical foundation for understanding machine learning and computational learning theory.

### Q: When did Leslie Valiant win the Turing Award?
A: Leslie Valiant won the Turing Award in 2010 for his transformative contributions to the theory of computation, including the development of computational learning theory.

### Q: Where does Leslie Valiant currently work?
A: Leslie Valiant has been a professor at Harvard University since 1982, where he continues his research in theoretical computer science.

## Why They Matter
Leslie Valiant's work fundamentally changed how we understand learning and computation. His PAC learning model provided the first rigorous mathematical framework for analyzing machine learning algorithms, enabling researchers to prove when and why learning is possible. This theoretical foundation has guided decades of practical machine learning development. His complexity theory contributions, particularly proving the #P-completeness of the permanent, established fundamental limits on what computers can efficiently compute. These insights influence everything from cryptography to optimization algorithms. Valiant's work bridges theory and practice, showing how abstract computational concepts can solve real-world problems in artificial intelligence and beyond.

## Notable For
- 2010 Turing Award recipient for contributions to computational learning theory
- Developed the Probably Approximately Correct (PAC) learning model
- Proved the #P-completeness of computing the permanent of a matrix
- Introduced the bulk synchronous parallel model for parallel computation
- Fellow of the Royal Society, National Academy of Sciences, and multiple other prestigious academies

## Body
### Early Life and Education
Leslie Valiant was born on March 28, 1949, in Budapest, Hungary. He moved to the United Kingdom and completed his undergraduate education at Imperial College London. He then pursued his doctoral studies at the University of Warwick, earning his Ph.D. in 1974.

### Academic Career
Valiant's academic career spans several prestigious institutions. He began as an assistant professor at Carnegie Mellon University (1973-1974), then moved to the University of Leeds (1974-1976) and the University of Edinburgh (1976-1982). Since 1982, he has been a professor at Harvard University, where he holds the T. Jefferson Coolidge Professorship of Computer Science and Applied Mathematics.

### Major Theoretical Contributions
Valiant's 1984 paper "A Theory of the Learnable" introduced the PAC learning model, which defines when a learning algorithm can produce results that are probably approximately correct. This framework has become fundamental to machine learning theory. His work on computational complexity includes proving that computing the permanent of a matrix is #P-complete, establishing important boundaries in what problems can be solved efficiently.

### Awards and Recognition
Beyond the Turing Award, Valiant has received numerous honors including the Knuth Prize (1997), EATCS Award (2008), and IMU Abacus Medal (1986). He is a Fellow of the Royal Society (elected 1991), the National Academy of Sciences (elected 2001), and the American Academy of Arts and Sciences. He was also named an ACM Fellow in 2012.

### Research Impact
Valiant's theoretical frameworks have influenced both academic research and practical applications in artificial intelligence. His work on parallel computing models has guided the development of distributed algorithms and high-performance computing systems. The PAC learning model continues to be used in analyzing and developing machine learning algorithms across academia and industry.

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## References

1. [Source](http://amturing.acm.org/award_winners/valiant_2612174.cfm)
2. Integrated Authority File
3. [Source](http://people.seas.harvard.edu/~valiant/bio.htm)
4. [Source](https://amturing.acm.org/award_winners/valiant_2612174.cfm)
5. [Source](https://www.seas.harvard.edu/person/leslie-valiant)
6. [Directory of Fellows of the Royal Society](https://royalsociety.org/people/leslie-valiant-12451/)
7. [Source](https://awards.acm.org/award_winners/valiant_2612174)
8. [Source](https://www.acm.org/media-center/2012/december/acm-fellows-named-for-computing-innovations-that-advance-technologies-in-information-age)
9. [Source](https://aaai.org/about-aaai/aaai-awards/the-aaai-fellows-program/elected-aaai-fellows/)
10. [Source](https://www.aaas.org/fellows/historic?field_last_name_value=All&name_combine=&field_institutional_affiliation_value=&field_address_city=All&field_address_when_elected_administrative_area=All&field_address_when_elected_country_code=All&field_year_elected=2008&field_primary_aaas_section=All&field_status_value=All&field_year_status_changed_value=&page=17)
11. [Source](https://www.aaas.org/fellows/historic?field_last_name_value=All&field_year_elected=2008&page=17)
12. [Source](https://www.amacad.org/new-members-2022)
13. [Source](https://www.ens-lyon.fr/indexation/mots-cles/doctorat-honoris-causa)
14. Mathematics Genealogy Project
15. International Standard Name Identifier
16. Virtual International Authority File
17. CiNii Research
18. MusicBrainz
19. www.nasonline.org
20. www.ae-info.org
21. MacTutor History of Mathematics archive
22. Freebase Data Dumps. 2013
23. Quora
24. [Source](http://www.nasonline.org/member-directory/living-member-list.html)