PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency.
Arun PadakandlaAbram MagnerPublished in: AISTATS (2022)
Keyphrases
- pac learning
- sample complexity
- pac learnable
- uniform distribution
- computational learning theory
- theoretical analysis
- regular languages
- sample size
- learning problems
- upper bound
- learning algorithm
- vc dimension
- learning theory
- concept classes
- pac model
- supervised learning
- generalization error
- special case
- active learning
- upper and lower bounds
- average case
- target function
- lower bound
- training examples
- class labels
- target concept
- statistical queries
- membership queries
- mistake bound
- multi class
- np hard
- feature space
- support vector