Lisa Hellerstein


Research Interests: Computational learning theory Machine learning Algorithms Complexity theory Discrete mathematics

Harvard University1984

Bachelor of Arts, Applied Mathematics/Computer Science

University of California at Berkeley1989

Doctor of Philosophy, Computer Science


  • Approximation Algorithms for Stochastic Boolean Function Evaluation and Stochastic Submodular Set Cover. Proceedings of the 25th ACM-SIAM Symposium on Discrete Algorithms (SODA), 2014 (with A. Deshpande and D. Kletenik).
  • Tight bounds on proper equivalence query learning of DNF. Proceedings of the 25th Conference on Learning Theory (COLT), 2012 (with D. Kletenik, L. Sellie and R.A. Servedio).
  • Algorithms for distributional and adversarial pipelined filter ordering problems. ACM Transactions on Algorithms, 5(2):1--34, 2009 (with A. Condon, A. Deshpande, and N. Wu).
  • Minimizing disjunctive normal form formulas and AC0 circuits given a truth table. SIAM Journal on Computing, 38(1):63--84, 2008 (with E. Allender, P. McCabe, T. Pitassi, M. E. Saks).
  • On the power of finite automata with both nondeterministic and probabilistic states. SIAM Journal on Computing 27(3): 739-762, 1998. (with A. Condon, S. Pottle, and A. Wigderson).
  • How many queries are needed to learn. JACM 43(5):840-862, 1996 (with K. Pillaipakkamnatt, D.Wilkins, and V. Raghavan).
  • Coding techniques for handling failures in large disk arrays. Algorithmica, 12:182-208, 1994 (with G. Gibson, R.M. Karp, R.H. Katz, and D.A. Patterson).

For a more complete list, with links: See journal papers and book articles and conference papers.


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