Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
A noise model on learning sets of strings
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Corrigendum to types of noise in data for concept learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Learning fallible finite state automata
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On-line learning of rectangles in noisy environments
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Statistical queries and faulty PAC oracles
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
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
Efficient agnostic PAC-learning with simple hypothesis
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning one-dimensional geometric patterns under one-sided random misclassification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning from a consistently ignorant teacher
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning linear threshold functions in the presence of classification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Efficient distribution-free learning of probabilistic concepts
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
Journal of Computer and System Sciences
Concept learning with geometric hypotheses
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
On learning bounded-width branching programs
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Exactly learning automata with small cover time
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
PAC learning intersections of halfspaces with membership queries (extended abstract)
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Exactly Learning Automata of Small Cover Time
Machine Learning - Special issue on the eighth annual conference on computational learning theory, (COLT '95)
Pruning Algorithms for Rule Learning
Machine Learning
Journal of the ACM (JACM)
Improved lower bounds for learning from noisy examples: an information-theoretic approach
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Noise-tolerant distribution-free learning of general geometric concepts
Journal of the ACM (JACM)
Efficient noise-tolerant learning from statistical queries
Journal of the ACM (JACM)
On PAC learning using Winnow, Perceptron, and a Perceptron-like algorithm
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Noise-tolerant learning, the parity problem, and the statistical query model
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
A neuroidal architecture for cognitive computation
Journal of the ACM (JACM)
Learning fixed-dimension linear thresholds from fragmented data
Information and Computation
Efficient distribution-free population learning of simple concepts
Annals of Mathematics and Artificial Intelligence
Toward effective knowledge acquisition with first-order logic induction
Journal of Computer Science and Technology
Theoretical Computer Science
Debiasing Training Data for Inductive Expert System Construction
IEEE Transactions on Knowledge and Data Engineering
Algorithms for Mining Distance-Based Outliers in Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
LIME: A System for Learning Relations
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Positive and Unlabeled Examples Help Learning
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Learning from Positive and Unlabeled Examples
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
Maximizing Agreements and CoAgnostic Learning
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
The Biases of Decision Tree Pruning Strategies
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
On Using Extended Statistical Queries to Avoid Membership Queries
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
PAC Learning from Positive Statistical Queries
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
A unified approach for mining outliers
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
Noise-tolerant learning, the parity problem, and the statistical query model
Journal of the ACM (JACM)
On the difficulty of approximately maximizing agreements
Journal of Computer and System Sciences
On using extended statistical queries to avoid membership queries
The Journal of Machine Learning Research
Shallow parsing using noisy and non-stationary training material
The Journal of Machine Learning Research
The Knowledge Engineering Review
Collaborative recommendation: A robustness analysis
ACM Transactions on Internet Technology (TOIT)
Classification and knowledge discovery in protein databases
Journal of Biomedical Informatics - Special issue: Biomedical machine learning
Stratification for scaling up evolutionary prototype selection
Pattern Recognition Letters
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers
IEEE Transactions on Knowledge and Data Engineering
Maximizing agreements and coagnostic learning
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning from positive and unlabeled examples
Theoretical Computer Science - Algorithmic learning theory (ALT 2000)
Active EM to reduce noise in activity recognition
Proceedings of the 12th international conference on Intelligent user interfaces
Semi-supervised learning integrated with classifier combination for word sense disambiguation
Computer Speech and Language
Learning Kernel Perceptrons on Noisy Data Using Random Projections
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Separating models of learning with faulty teachers
Theoretical Computer Science
Nearest neighbor editing aided by unlabeled data
Information Sciences: an International Journal
Semi-supervised document retrieval
Information Processing and Management: an International Journal
For a few dollars less: identifying review pages sans human labels
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
ILP with noise and fixed example size: a Bayesian approach
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
A critique of the valiant model
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Learning from partial observations
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Category translation: learning to understand information on the internet
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Learning to reason the non monotonic case
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Learning with annotation noise
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
A study of the effect of different types of noise on the precision of supervised learning techniques
Artificial Intelligence Review
Partial observability and learnability
Artificial Intelligence
Context cells: towards lifelong learning in activity recognition systems
EuroSSC'09 Proceedings of the 4th European conference on Smart sensing and context
Probably approximately correct learning
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Analyses of instance-based learning algorithms
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Classifier learning from noisy data as probabilistic evidence combination
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Oblivious PAC learning of concept hierarchies
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
An analysis of Bayesian classifiers
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Learning from an approximate theory and noisy examples
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Algorithms and theory of computation handbook
Agreement-based semi-supervised learning for skull stripping
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
The regularized least squares algorithm and the problem of learning halfspaces
Information Processing Letters
Learning Multi-modal Similarity
The Journal of Machine Learning Research
Software defect detection with rocus
Journal of Computer Science and Technology
A new co-training-style random forest for computer aided diagnosis
Journal of Intelligent Information Systems
Calculation and optimization of thresholds for sets of software metrics
Empirical Software Engineering
Discrete decision tree induction to avoid overfitting on categorical data
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
Generalized learning problems and applications to non-commutative cryptography
ProvSec'11 Proceedings of the 5th international conference on Provable security
Identifying mislabeled training data with the aid of unlabeled data
Applied Intelligence
On noise-tolerant learning of sparse parities and related problems
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Active learning in the non-realizable case
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Mining Recurring Concept Drifts with Limited Labeled Streaming Data
ACM Transactions on Intelligent Systems and Technology (TIST)
Learning attribute-efficiently with corrupt oracles
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Learning juntas in the presence of noise
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Sample-based software defect prediction with active and semi-supervised learning
Automated Software Engineering
A noise-tolerant graphical model for ranking
Information Processing and Management: an International Journal
A study of the robustness of KNN classifiers trained using soft labels
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
A logical analysis of banks' financial strength ratings
Expert Systems with Applications: An International Journal
DCPE co-training for classification
Neurocomputing
On learning finite-state quantum sources
Quantum Information & Computation
Semi-supervised ensemble learning of data streams in the presence of concept drift
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Journal of Data and Information Quality (JDIQ)
An experimental comparison of real and artificial deception using a deception generation model
Decision Support Systems
Variational multinomial logit gaussian process
The Journal of Machine Learning Research
Classification of Unseen Examples under Uncertainty
Fundamenta Informaticae
A hybrid generative/discriminative method for semi-supervised classification
Knowledge-Based Systems
PAC-Learning with general class noise models
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
A Computational Learning Theory of Active Object Recognition Under Uncertainty
International Journal of Computer Vision
Revisiting lightweight authentication protocols based on hard learning problems
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
Inter-training: Exploiting unlabeled data in multi-classifier systems
Knowledge-Based Systems
ALFRED: crowd assisted data extraction
Proceedings of the 22nd international conference on World Wide Web companion
Security analysis of online centroid anomaly detection
The Journal of Machine Learning Research
Convex and scalable weakly labeled SVMs
The Journal of Machine Learning Research
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The basic question addressed in this paper is: how can a learning algorithm cope with incorrect training examples? Specifically, how can algorithms that produce an “approximately correct” identification with “high probability” for reliable data be adapted to handle noisy data? We show that when the teacher may make independent random errors in classifying the example data, the strategy of selecting the most consistent rule for the sample is sufficient, and usually requires a feasibly small number of examples, provided noise affects less than half the examples on average. In this setting we are able to estimate the rate of noise using only the knowledge that the rate is less than one half. The basic ideas extend to other types of random noise as well. We also show that the search problem associated with this strategy is intractable in general. However, for particular classes of rules the target rule may be efficiently identified if we use techniques specific to that class. For an important class of formulas – the k-CNF formulas studied by Valiant – we present a polynomial-time algorithm that identifies concepts in this form when the rate of classification errors is less than one half.