On the Hardness of PAC-learning stabilizer States with Noise.
Aravind GollakotaDaniel LiangPublished in: CoRR (2021)
Keyphrases
- pac learning
- agnostic learning
- learning theory
- attribute noise
- uniform distribution
- computational learning theory
- classification noise
- sample complexity
- learning problems
- membership queries
- sample size
- pac learnability
- target concept
- concept classes
- decision lists
- noisy environments
- noise level
- gaussian noise
- term dnf
- mistake bound
- learning dnf
- statistical queries
- vc dimension
- theoretical analysis
- concept class
- noise model
- boolean functions
- phase transition
- information theoretic
- computational complexity
- machine learning