Sharp uniform convergence bounds through empirical centralization.
Cyrus CousinsMatteo RiondatoPublished in: NeurIPS (2020)
Keyphrases
- uniform convergence
- covering numbers
- empirical risk minimization
- sufficient conditions
- learning rate
- vc dimension
- risk minimization
- empirical risk
- upper and lower bounds
- reproducing kernel hilbert space
- generalization bounds
- real valued
- statistical learning theory
- sample complexity
- bipartite ranking
- large deviations
- generalization error
- gaussian kernels
- data dependent
- upper bound
- learning algorithm
- learning theory
- ranking functions