Small-bias probability spaces: efficient constructions and applications
SIAM Journal on Computing
Linear time deterministic learning of k-term DNF
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Constant depth circuits, Fourier transform, and learnability
Journal of the ACM (JACM)
Weakly learning DNF and characterizing statistical query learning using Fourier analysis
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
SIAM Journal on Computing
When won't membership queries help?
Selected papers of the 23rd annual ACM symposium on Theory of computing
Fast learning of k-term DNF formulas with queries
Journal of Computer and System Sciences - Special issue on selected papers presented at the 24th annual ACM symposium on the theory of computing (STOC '92)
Exact learning Boolean functions via the monotone theory
Information and Computation
Generalized teaching dimensions and the query complexity of learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Asking questions to minimize errors
Journal of Computer and System Sciences
How many queries are needed to learn?
Journal of the ACM (JACM)
A subexponential exact learning algorithm for DNF using equivalence queries
Information Processing Letters
On the limits of proper learnability of subclasses of DNF formulas
Machine Learning - Special issue on COLT '94
A simple algorithm for learning O (log n)-term DNF
Information Processing Letters
An efficient membership-query algorithm for learning DNF with respect to the uniform distribution
Journal of Computer and System Sciences
Complexity theoretic hardness results for query learning
Computational Complexity
Bounds to Complexities of Networks for Sorting and for Switching
Journal of the ACM (JACM)
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Machine Learning
Machine Learning
Oracles in Sigmap2 are Sufficient for Exact Learning
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Abstract Combinatorial Characterizations of Exact Learning via Queries
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Learning DNF by Approximating Inclusion-Exclusion Formulae
COCO '99 Proceedings of the Fourteenth Annual IEEE Conference on Computational Complexity
The Minimum Equivalent DNF Problem and Shortest Implicants
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Hardness of Approximating Minimization Problems
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
On the applications of multiplicity automata in learning
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
On the Proper Learning of Axis Parallel Concepts
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
On the proper learning of axis-parallel concepts
The Journal of Machine Learning Research
Exact learning of DNF formulas using DNF hypotheses
Journal of Computer and System Sciences - Special issue on COLT 2002
Hardness of approximate two-level logic minimization and PAC learning with membership queries
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Theoretical Computer Science
Polynomial certificates for propositional classes
Information and Computation
The complexity of properly learning simple concept classes
Journal of Computer and System Sciences
Hardness of approximate two-level logic minimization and PAC learning with membership queries
Journal of Computer and System Sciences
Polynomial certificates for propositional classes
Information and Computation
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(MATH) We show the following: For any &egr; ρ 0, (log n)(3 + &egr;)-term DNF cannot be polynomial-query learned with membership and strongly proper equivalence queries. For any function f(n) &egr; o [box] (&frac;√n \over log n) [end-box] , m-term DNF formulas cannot be polynomial-query learned by a membership and equivalence query algorithm that uses m &dotfill; f(n)-term DNF formulas as hypotheses. Read-thrice DNF formulas are not learnable with membership and proper equivalence queries. log n-term DNF formulas can be polynomial-query learned with membership and proper equivalence queries. (This complements a result of Bshouty, Goldman, Hancock, and Matar stating that [box] √log n [end-box] -term DNF can be so learned in polynomial time. .Using purely information theoretic techniques, these results extend and improve what is currently known. (For example, a weaker version of (a) was known only under a barely plausible complexity theoretic assumption, (b) was previously unknown, and (c) was known under the assumption P ‡ NP.)