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Dana Angluin

Dana Angluin
Fields Computer Science
Institutions Yale University
Alma mater University of California, Berkeley
Doctoral advisor Template:If empty
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:

See also

References

  1. ^ D Angluin (1976). "An Application of the Theory of Computational Complexity to the Study of Inductive Inference." Available from ProQuest Dissertations & Theses Global. (302813707)
  2. ^ [1],COLT '89 Proceedings
  3. ^ [2], COLT '02 Proceedings
  4. ^ [3], COLT '08 Proceedings
  5. ^ [4], Information and Computation Volume 2 Issue 1
  6. ^ [5], Information and Computation Volume 99 Issue 1

External links