Dana Angluin
| Dana Angluin | |
|---|---|
| Fields | Computer Science |
| Institutions | Yale University |
| Alma mater | University of California, Berkeley |
| Doctoral advisor | Manuel Blum |
| Known for |
L* Algorithm Query learning Exact learning |
Dana Angluin is a professor of computer science at Yale University. She is known for her foundational contributions to computational learning theory.
Biography
Professor Angluin is interested in machine learning and computational learning theory. Algorithmic modeling and analysis of learning tasks gives insight into the phenomena of learning, and suggests avenues for the creation of tools to help people learn, and for the design of "smarter" software and artificial agents that flexibly adapt their behavior. Professor Angluin’s thesis[1] was among the first work to apply computational complexity theory to the field of inductive inference. Her work on learning from positive data reversed a previous dismissal of that topic, and established a flourishing line of research. Her work on learning with queries established the models and the foundational results for learning with membership queries. Recently, her work has focused on the areas of coping with errors in the answers to queries, map-learning by mobile robots, and fundamental questions in modeling the interaction of a teacher and a learner.
Professor Angluin helped found the Computational Learning Theory (COLT) conference, and has served on program committees for COLT[2][3][4] and on the COLT Steering committee. She served as an area editor for Information and Computation from 1989-1992.[5][6] She organized Yale's Computer Science Department’s Perlis Symposium in April 2001: "From Statistics to Chat: Trends in Machine Learning". She is a member of the Association for Computing Machinery and the Association for Women in Mathematics.
Work
Representative Publications:
- Dana Angluin (Nov 2001). "Queries revisited (Invited paper)". In Naoki Abe, Roni Khardon, Thomas Zeugmann. Algorithmic Learning Theory — 12th International Conference. LNCS 2225. Springer. pp. 12–31.
- "Robot navigation with distance queries," with J. Westbrook and W. Zhu, SIAM Journal on Computing, 30:110-144, 2000.
- Dana Angluin (1987). "Learning Regular Sets from Queries and Counter-Examples" (PDF). Information and Control 75: 87–106. doi:10.1016/0890-5401(87)90052-6.
- Dana Angluin (Aug 1987). Learning k-Bounded Context-Free Grammars (PDF) (Technical report). Yale University. p. 13. 557.
- Dana Angluin (1980). "Finding Patterns Common to a Set of Strings" (PDF). 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: 117–135. doi:10.1016/s0019-9958(80)90285-5.
- 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
- ↑ D Angluin (1976). "An Application of the Theory of Computational Complexity to the Study of Inductive Inference." Available from ProQuest Dissertations & Theses Global. (302813707)
- ↑ , COLT '89 Proceedings
- ↑ , COLT '02 Proceedings
- ↑ , COLT '08 Proceedings
- ↑ , Information and Computation Volume 2 Issue 1
- ↑ , Information and Computation Volume 99 Issue 1
External links
- Angluin's home page at Yale University
- Angluin's Google Scholar listing
- "Hack to the Future." Yale Daily News retrieved 4/16/2015