Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
On the necessity of Occam algorithms
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Learning DNF formulae under classes of probability distributions
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Characterizations of learnability for classes of {O, …, n}-valued functions
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Lower bounds for PAC learning with queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
General bounds on the number of examples needed for learning probabilistic concepts
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Rigorous learning curve bounds from statistical mechanics
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Simulating access to hidden information while learning
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
From noise-free to noise-tolerant and from on-line to batch learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Sample sizes for sigmoidal neural networks
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
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
More theorems about scale-sensitive dimensions and learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Specification and simulation of statistical query algorithms for efficiency and noise tolerance
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant learning near the information-theoretic bound
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Noise-tolerant distribution-free learning of general geometric concepts
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
On the complexity of learning from drifting distributions
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
On restricted-focus-of-attention learnability of Boolean functions
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Strong minimax lower bounds for learning
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Approximating hyper-rectangles: learning and pseudo-random sets
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Computational sample complexity
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Improved lower bounds for learning from noisy examples: an information-theoretic approach
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Strong Minimax Lower Bounds for Learning
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
On Restricted-Focus-of-Attention Learnability of Boolean Functions
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Computational sample complexity and attribute-efficient learning
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Efficient exploration for optimizing immediate reward
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Sample-efficient strategies for learning in the presence of noise
Journal of the ACM (JACM)
Improved bounds on the sample complexity of learning
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
A neuroidal architecture for cognitive computation
Journal of the ACM (JACM)
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Information Processing Letters
Mathematical Modelling of Generalization
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Structural Complexity and Neural Networks
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Coherent Concepts, Robust Learning
SOFSEM '99 Proceedings of the 26th Conference on Current Trends in Theory and Practice of Informatics on Theory and Practice of Informatics
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Connectionist and evolutionary models for learning, discovering and forecasting software effort
Managing data mining technologies in organizations
Cost-Sensitive Learning by Cost-Proportionate Example Weighting
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Function Learning from Interpolation
Combinatorics, Probability and Computing
Theoretical Computer Science - Special issue: Algorithmic learning theory
Journal of Computer and System Sciences - STOC 2001
Generalization Error Bounds for Threshold Decision Lists
The Journal of Machine Learning Research
On data classification by iterative linear partitioning
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
Some connections between learning and optimization
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
Complexity parameters for first order classes
Machine Learning
A new PAC bound for intersection-closed concept classes
Machine Learning
Discriminative learning can succeed where generative learning fails
Information Processing Letters
Aspects of discrete mathematics and probability in the theory of machine learning
Discrete Applied Mathematics
A Uniform Lower Error Bound for Half-Space Learning
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Journal of the ACM (JACM)
Shifting: One-inclusion mistake bounds and sample compression
Journal of Computer and System Sciences
Using the doubling dimension to analyze the generalization of learning algorithms
Journal of Computer and System Sciences
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The complexity of theory revision
Artificial Intelligence
On data classification by iterative linear partitioning
Discrete Applied Mathematics
Some connections between learning and optimization
Discrete Applied Mathematics
A discriminative model for semi-supervised learning
Journal of the ACM (JACM)
Journal of Network and Computer Applications
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Algorithms and theory of computation handbook
An improved lower bound on query complexity for quantum PAC learning
Information Processing Letters
Theoretical Computer Science
Bounds on the sample complexity for private learning and private data release
TCC'10 Proceedings of the 7th international conference on Theory of Cryptography
A PAC-Style model for learning from labeled and unlabeled data
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Projection-Based PILP: computational learning theory with empirical results
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
PAC learnability of rough hypercuboid classifier
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
MFCS'07 Proceedings of the 32nd international conference on Mathematical Foundations of Computer Science
Characterizing the sample complexity of private learners
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
On the necessity of irrelevant variables
The Journal of Machine Learning Research
Supervised learning and Co-training
Theoretical Computer Science
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