Communications of the ACM
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
A hard-core predicate for all one-way functions
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Boosting a weak learning algorithm by majority
COLT '90 Proceedings of the third annual workshop on Computational learning theory
An O(nlog log n) learning algorithm for DNF under the uniform distribution
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
An improved boosting algorithm and its implications on learning complexity
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Learning Boolean Functions in an Infinite Attribute Space
Machine Learning
Small-bias probability spaces: efficient constructions and applications
SIAM Journal on Computing
Learning decision trees using the Fourier spectrum
SIAM Journal on Computing
Learning in the presence of finitely or infinitely many irrelevant attributes
Journal of Computer and System Sciences
Attribute-efficient learning in query and mistake-bound models
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
An efficient membership-query algorithm for learning DNF with respect to the uniform distribution
Journal of Computer and System Sciences
Adaptive versus nonadaptive attribute-efficient learning
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Introduction to Coding Theory
Machine Learning
Machine Learning
Optimal Attribute-Efficient Learning of Disjunction, Parity and Threshold Functions
EuroCOLT '97 Proceedings of the Third European Conference on Computational Learning Theory
Boosting and Hard-Core Set Construction
Machine Learning
Approximate Location of Relevant Variables under the Crossover Distribution
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
Quantum DNF Learnability Revisited
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Proclaiming Dictators and Juntas or Testing Boolean Formulae
APPROX '01/RANDOM '01 Proceedings of the 4th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems and 5th International Workshop on Randomization and Approximation Techniques in Computer Science: Approximation, Randomization and Combinatorial Optimization
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
On Boosting with Optimal Poly-Bounded Distributions
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
On Learning Monotone DNF under Product Distributions
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
On boosting with polynomially bounded distributions
The Journal of Machine Learning Research
Optimally-smooth adaptive boosting and application to agnostic learning
The Journal of Machine Learning Research
Learning intersections and thresholds of halfspaces
Journal of Computer and System Sciences - Special issue on FOCS 2002
On learning monotone DNF under product distributions
Information and Computation
Learning functions of k relevant variables
Journal of Computer and System Sciences - Special issue: STOC 2003
Learning DNF from random walks
Journal of Computer and System Sciences - Special issue: Learning theory 2003
Separating Models of Learning from Correlated and Uncorrelated Data
The Journal of Machine Learning Research
Property Testing: A Learning Theory Perspective
Foundations and Trends® in Machine Learning
On attribute efficient and non-adaptive learning of parities and DNF expressions
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Separating models of learning from correlated and uncorrelated data
COLT'05 Proceedings of the 18th annual conference on Learning Theory
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