Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression.
Daniel KiferAdam D. SmithAbhradeep ThakurtaPublished in: COLT (2012)
Keyphrases
- convex optimization
- empirical risk minimization
- high dimensional
- uniform convergence
- regression model
- model selection
- reproducing kernel hilbert space
- vc dimension
- generalization bounds
- interior point methods
- low dimensional
- low rank
- dimensionality reduction
- linear regression
- total variation
- feature space
- high dimensional data
- primal dual
- regression problems
- special case
- convex optimization problems
- regression function
- input space
- ridge regression
- regression methods
- variable selection
- upper bound
- data points
- training samples
- worst case
- lower bound