Dana Angluin

Dana Angluin is a professor of computer science at Yale University. She is known for foundational work in computational learning theory [2][3][4] and distributed computing.[5]

Dana Angluin
Alma materUniversity of California, Berkeley
Known forL* Algorithm
Query learning
Exact learning
Population protocols
Scientific career
FieldsComputer Science Machine Learning
InstitutionsYale University
ThesisAn Application of the Theory of Computational Complexity to the Study of Inductive Inference (1976)
Doctoral advisorManuel Blum[1]
Doctoral studentsEhud Shapiro

Education

Angluin received her B.A. and Ph.D. at University of California, Berkeley.[6] Her thesis, entitled "An application of the theory of computational complexity to the study of inductive inference" [7] was one of the first works to apply complexity theory to the field of inductive inference.[8] Angluin joined the faculty at Yale in 1979.[8]

Research

Angluin has written highly cited papers on computational learning theory, where she studied learning from noisy examples [4] and learning regular sets from queries and counterexamples,[3] distributed computing, where she co-invented the population protocol model and studied the problem of consensus,[5][9] and probabilistic algorithms, where she studied randomized algorithms for Hamiltonian circuits and matchings.[10][8][11]

Angluin helped found the Computational Learning Theory (COLT) conference, and has served on program committees and steering committees for COLT[12][13][14] She served as an area editor for Information and Computation from 1989–1992.[15][16] She organized Yale's Computer Science Department's Perlis Symposium in April 2001: "From Statistics to Chat: Trends in Machine Learning".[17] She is a member of the Association for Computing Machinery and the Association for Women in Mathematics.

Angluin has also published works on Ada Lovelace and her involvement with the Analytical Engine.[18]

Selected Publications
  • Dana Angluin (1988). Queries and concept learning. Machine Learning. 2 (4): 319-342.
  • Dana Angluin (1987). "Learning Regular Sets from Queries and Counter-Examples" (PDF). Information and Control. 75 (2): 87–106. doi:10.1016/0890-5401(87)90052-6. Archived from the original (PDF) on 2013-12-02.
  • Dana Angluin and Philip Laird (1988). Learning from noisy examples. Machine Learning 2 (4), 343-370.
  • Dana Angluin and Leslie Valiant (1979). Fast probabilistic algorithms for Hamiltonian circuits and matchings. Journal of Computer and system Sciences 18 (2), 155-193
  • Dana Angluin (1980). "Finding Patterns Common to a Set of Strings". Journal of Computer and System Sciences. 21: 46–62. doi:10.1016/0022-0000(80)90041-0.
  • Dana Angluin (1980). "Inductive Inference of Formal Languages from Positive Data" (PDF). Information and Control. 45 (2): 117–135. doi:10.1016/s0019-9958(80)90285-5.
  • Dana Angluin, James Aspnes, Zoë Diamadi, Michael J Fischer, René Peralta (2004). Computation in networks of passively mobile finite-state sensors. Distributed computing 18 (4), 235-253.
  • Dana Angluin (1976). An Application of the Theory of Computational Complexity to the Study of Inductive Inference (Ph.D.). University of California at Berkeley.

See also

References
  1. Dana Angluin at the Mathematics Genealogy Project
  2. Angluin, Dana (April 1988). "Queries and concept learning". Machine Learning. 2 (4): 319–342. doi:10.1007/bf00116828. ISSN 0885-6125. S2CID 11357867.
  3. Angluin, Dana (November 1987). "Learning regular sets from queries and counterexamples". Information and Computation. 75 (2): 87–106. doi:10.1016/0890-5401(87)90052-6. ISSN 0890-5401.
  4. Angluin, Dana; Laird, Philip (April 1988). "Learning from noisy examples". Machine Learning. 2 (4): 343–370. doi:10.1007/bf00116829. ISSN 0885-6125. S2CID 29767720.
  5. Angluin, Dana; Aspnes, James; Diamadi, Zoë; Fischer, Michael J.; Peralta, René (2006-03-01). "Computation in networks of passively mobile finite-state sensors". Distributed Computing. 18 (4): 235–253. doi:10.1007/s00446-005-0138-3. ISSN 1432-0452. S2CID 2802601.
  6. "Dana Angluin, B.A., Ph.D. University of California at Berkeley, 1969, 1976. Joined Yale Faculty 1979. | Computer Science". cpsc.yale.edu. Retrieved 2020-11-08.
  7. Angluin, Dana Charmian (1976). An Application of the Theory of Computational Complexity to the Study of Inductive Inference (PhD Thesis thesis). University of California, Berkeley.
  8. "Dana Angluin, B.A., Ph.D. University of California at Berkeley, 1969, 1976. Joined Yale Faculty 1979. | Computer Science". cpsc.yale.edu. Retrieved 2016-12-11.
  9. Angluin, Dana; Aspnes, James; Eisenstat, David (2008-07-01). "A simple population protocol for fast robust approximate majority". Distributed Computing. 21 (2): 87–102. doi:10.1007/s00446-008-0059-z. ISSN 1432-0452. S2CID 2652934.
  10. Angluin, Dana; Valiant, Leslie G. (1977). "Fast probabilistic algorithms for hamiltonian circuits and matchings". Proceedings of the Ninth Annual ACM Symposium on Theory of Computing - STOC '77. New York, New York, USA: ACM Press: 30–41. doi:10.1145/800105.803393. S2CID 2624407.
  11. D Angluin (1976). "An Application of the Theory of Computational Complexity to the Study of Inductive Inference." Available from ProQuest Dissertations & Theses Global. (302813707)
  12. , COLT '89 Proceedings
  13. , COLT '02 Proceedings
  14. , COLT '08 Proceedings
  15. "Editorial Board". Information and Computation. 82 (1): i. 1989. doi:10.1016/0890-5401(89)90061-8.
  16. "Editorial Board". Information and Computation. 99 (1): i. 1992. doi:10.1016/0890-5401(92)90023-9.
  17. "Symposium will explore 'trends in machine learning'". Yale Bulletin and Calendar. April 20, 2001. Archived from the original on April 18, 2009.
  18. Case, Bettye Anne; Leggett, Anne M. (2005). Complexities: Women in Mathematics. Princeton University Press. p. 60. ISBN 9781400880164.
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