Communications of the ACM
How to generate cryptographically strong sequences of pseudo-random bits
SIAM Journal on Computing
How to construct random functions
Journal of the ACM (JACM)
Learning regular sets from queries and counterexamples
Information and Computation
Computational limitations on learning from examples
Journal of the ACM (JACM)
Prediction-preserving reducibility
Journal of Computer and System Sciences - 3rd Annual Conference on Structure in Complexity Theory, June 14–17, 1988
Coherent functions and program checkers
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
When won't membership queries help?
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
Information and Computation
Cryptographic hardness of distribution-specific learning
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
The Complexity of Decision Versus Search
SIAM Journal on Computing
On being incoherent without being very hard
Computational Complexity
An optimal parallel algorithm for learning DFA
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
The power of adaptiveness and additional queries in random-self-reductions
Computational Complexity
Being taught can be faster than asking questions
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant parallel learning of geometric concepts
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
P-selective sets and reducing search to decision vs. self-reducibility
Journal of Computer and System Sciences
Exact Learning of Formulas in Parallel
Machine Learning
Perfectly one-way probabilistic hash functions (preliminary version)
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
A Pseudorandom Generator from any One-way Function
SIAM Journal on Computing
Machine Learning
Machine Learning
Efficient NC algorithms for set cover with applications to learning and geometry
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
One-way functions are essential for complexity based cryptography
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
On the exact learning of formulas in parallel
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
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We assume wlog. that every learning algorithm with membership and equivalence queries proceeds in rounds. In each round it puts in parallel a polynomial number of queries and after receiving the answers, it performs internal computations before starting the next round. The query depth is defined by the number of rounds. In this paper we show that, assuming the existence of cryptographic one-way functions, for any fixed polynomial d(n) there exists a concept class that is efficiently and exactly learnable with membership queries in query depth d(n) + 1, but cannot be weakly predicted with membership and equivalence queries in depth d(n). Hence, concerning the query depth, efficient learning algorithms for this concept class cannot be parallelized at all. We also discuss some applications to random self-reductions and coherent sets.