Sample Complexity of Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization.
Zhe WangYi ZhouYingbin LiangGuanghui LanPublished in: CoRR (2018)
Keyphrases
- sample complexity
- optimization problems
- theoretical analysis
- covering numbers
- upper bound
- image restoration and reconstruction
- vc dimension
- pac learning
- generalization error
- learning algorithm
- learning problems
- special case
- lower bound
- supervised learning
- active learning
- concept classes
- training examples
- risk minimization
- sample size
- reproducing kernel hilbert space
- kernel machines
- uniform convergence
- data sets
- learning tasks
- markov random field
- pairwise