Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
Learnability by fixed distributions
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Decision theoretic generalizations of the PAC model for neural net and other learning applications
Information and Computation
Active Learning Using Arbitrary Binary Valued Queries
Machine Learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Active learning in the non-realizable case
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
On the sample complexity of PAC learning half-spaces against the uniform distribution
IEEE Transactions on Neural Networks
Hierarchical sampling for active learning
Proceedings of the 25th international conference on Machine learning
Journal of Computer and System Sciences
Importance weighted active learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Efficient Coverage of Case Space with Active Learning
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
A discriminative model for semi-supervised learning
Journal of the ACM (JACM)
On active learning of record matching packages
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
On the Foundations of Noise-free Selective Classification
The Journal of Machine Learning Research
d-Confidence: an active learning strategy which efficiently identifies small classes
ALNLP '10 Proceedings of the NAACL HLT 2010 Workshop on Active Learning for Natural Language Processing
Bayesian active learning using arbitrary binary valued queries
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Theoretical Computer Science
Theoretical Computer Science
Smoothness, Disagreement Coefficient, and the Label Complexity of Agnostic Active Learning
The Journal of Machine Learning Research
Supervised learning and co-training
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Efficient Learning with Partially Observed Attributes
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Active learning via perfect selective classification
The Journal of Machine Learning Research
Active sampling for entity matching
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Activized learning: transforming passive to active with improved label complexity
The Journal of Machine Learning Research
A theory of transfer learning with applications to active learning
Machine Learning
Active Sampling for Entity Matching with Guarantees
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on ACM SIGKDD 2012
Selective sampling and active learning from single and multiple teachers
The Journal of Machine Learning Research
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Supervised learning and Co-training
Theoretical Computer Science
Efficient active learning of halfspaces: an aggressive approach
The Journal of Machine Learning Research
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We study the label complexity of pool-based active learning in the agnostic PAC model. Specifically, we derive general bounds on the number of label requests made by the A2 algorithm proposed by Balcan, Beygelzimer & Langford (Balcan et al., 2006). This represents the first nontrivial general-purpose upper bound on label complexity in the agnostic PAC model.