Communications of the ACM
PP is as hard as the polynomial-time hierarchy
SIAM Journal on Computing
Almost everywhere high nonuniform complexity
Journal of Computer and System Sciences
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
Cryptographic lower bounds for learnability of Boolean functions on the uniform distribution
Journal of Computer and System Sciences
Mathematical metaphysics of randomness
Theoretical Computer Science - Special issue Kolmogorov complexity
Complexity theoretic hardness results for query learning
Computational Complexity
A Generalization of Resource-Bounded Measure, with Application to the BPP vs. EXP Problem
SIAM Journal on Computing
Machine Learning
Machine Learning
Superpolynomial Circuits, Almost Sparse Oracles and the Exponential Hierarchy
Proceedings of the 12th Conference on Foundations of Software Technology and Theoretical Computer Science
Some connections between nonuniform and uniform complexity classes
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Online Learning and Resource-Bounded Dimension: Winnow Yields New Lower Bounds for Hard Sets
SIAM Journal on Computing
Efficient learning algorithms yield circuit lower bounds
Journal of Computer and System Sciences
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This paper extends and improves work of Fortnow and Klivans [5], who showed that if a circuit class C has an efficient learning algorithm in Angluin's model of exact learning via equivalence and membership queries [2], then we have the lower bound EXPNP ⊈ C. We use entirely different techniques involving betting games [4] to remove the NP oracle and improve the lower bound to EXP ⊈ C. This shows that it is even more difficult to design a learning algorithm for C than the results of Fortnow and Klivans indicated.