Dana Angluin

Dana Angluin
Alma materUniversity of California, Berkeley (BA, PhD)
Known for
  • L* Algorithm
  • Query learning
  • Exact learning
  • Population protocols
Scientific career
Fields
InstitutionsYale University
Thesis An Application of the Theory of Computational Complexity to the Study of Inductive Inference  (1976)
Doctoral advisorManuel Blum[1]
Doctoral studentsEhud Shapiro

Dana Angluin is a professor emeritus of computer science at Yale University.[2] She is known for foundational work in computational learning theory[3][4][5] and distributed computing.[6]

  1. ^ Dana Angluin at the Mathematics Genealogy Project
  2. ^ "Dana Angluin, B.A., Ph.D. University of California at Berkeley, 1969, 1976. Joined Yale Faculty 1979. | Computer Science". cpsc.yale.edu. Retrieved 2021-12-01.
  3. ^ Angluin, Dana (April 1988). "Queries and concept learning". Machine Learning. 2 (4): 319–342. doi:10.1007/bf00116828. ISSN 0885-6125. S2CID 11357867.
  4. ^ 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.
  5. ^ 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.
  6. ^ 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.