On the Hardness of PAC-learning Stabilizer States with Noise.
Aravind GollakotaDaniel LiangPublished in: Quantum (2022)
Keyphrases
- pac learning
- agnostic learning
- learning theory
- attribute noise
- uniform distribution
- classification noise
- computational learning theory
- sample size
- sample complexity
- learning problems
- target concept
- pac learnability
- concept classes
- mistake bound
- noise level
- decision lists
- noise model
- membership queries
- computational complexity
- concept class
- noisy data
- gaussian noise
- worst case
- lower bound
- vc dimension
- pac model
- boolean functions
- information theoretic