Differentially Private Stochastic Convex Optimization under a Quantile Loss Function.
Du ChenGeoffrey A. ChuaPublished in: ICML (2023)
Keyphrases
- convex optimization
- loss function
- differentially private
- hinge loss
- differential privacy
- pairwise
- interior point methods
- norm regularization
- low rank
- support vector
- primal dual
- learning to rank
- convex optimization problems
- reproducing kernel hilbert space
- total variation
- convex programming
- risk minimization
- coordinate descent method
- pairwise constraints
- privacy preserving
- machine learning
- dimensionality reduction
- active learning