Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm
Nick Littlestone low
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Citation edge evidence
- Natural Language Processing (almost) from Scratch→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Natural Language Processing (almost) from Scratch→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- A survey on concept drift adaptation→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Selection of relevant features and examples in machine learning→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Prediction, Learning, and Games→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Understanding Machine Learning: From Theory To Algorithms→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Irrelevant Features and the Subset Selection Problem→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Learnability and the Vapnik-Chervonenkis dimension→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Increased rates of convergence through learning rate adaptation→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Queries and Concept Learning→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- What Size Net Gives Valid Generalization?→Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold AlgorithmLegacy edge — source detail unavailable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm→Parallel Distributed ProcessingLegacy edge — source detail unavailable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm→On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesLegacy edge — source detail unavailable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm→Queries and Concept LearningLegacy edge — source detail unavailable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm→Generalization as searchLegacy edge — source detail unavailable
- Feature selection, L 1 vs. L 2 regularization, and rotational invariance→Selection of relevant features and examples in machine learningLegacy edge — source detail unavailable
- Selection of relevant features and examples in machine learning→Irrelevant Features and the Subset Selection ProblemLegacy edge — source detail unavailable
- Selection of relevant features and examples in machine learning→Generalization as searchLegacy edge — source detail unavailable
- Selection of relevant features and examples in machine learning→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
- A survey on concept drift adaptation→Prediction, Learning, and GamesLegacy edge — source detail unavailable
- Queries and Concept Learning→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
- Learnability and the Vapnik-Chervonenkis dimension→Queries and Concept LearningLegacy edge — source detail unavailable
- Learnability and the Vapnik-Chervonenkis dimension→What Size Net Gives Valid Generalization?Legacy edge — source detail unavailable
- Learnability and the Vapnik-Chervonenkis dimension→On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesLegacy edge — source detail unavailable
- What Size Net Gives Valid Generalization?→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
- Understanding Machine Learning: From Theory To Algorithms→Prediction, Learning, and GamesLegacy edge — source detail unavailable
- Understanding Machine Learning: From Theory To Algorithms→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Parallel Distributed Processing | 1986 | 15,411 |
| On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities | 1971 | 2,435 |
| Learnability and the Vapnik-Chervonenkis dimension | 1989 | 1,855 |
| Queries and Concept Learning | 1988 | 1,636 |
| Generalization as search | 1982 | 1,442 |
What cites it, inside the corpus
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Topics
| Machine Learning and Algorithms | Computer Science |
| Algorithms and Data Compression | Computer Science |
| Machine Learning and Data Classification | Computer Science |
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