Deep Learnability: Using Neural Networks to Quantify Language Similarity and Learnability.
Clara CohenCatherine F. HighamSyed Waqar NabiPublished in: Frontiers Artif. Intell. (2020)
Keyphrases
- neural network
- pattern languages
- finite automata
- regular languages
- boolean functions
- learning algorithm
- uniform distribution
- pattern recognition
- inductive inference
- learning from positive data
- pac learnability
- uniform convergence
- similarity measure
- euclidean distance
- sufficient conditions
- distance measure
- vapnik chervonenkis dimension
- programming language
- dnf formulas
- artificial neural networks
- inductive logic programming
- pac learning
- positive data
- regular expressions
- multi layer
- linear separability
- machine learning
- support vector machine
- grammatical inference
- efficient learning
- membership queries
- back propagation