On the Privacy of Noisy Stochastic Gradient Descent for Convex Optimization.
Jason M. AltschulerJinho BokKunal TalwarPublished in: SIAM J. Comput. (2024)
Keyphrases
- convex optimization
- stochastic gradient descent
- least squares
- loss function
- matrix factorization
- step size
- random forests
- support vector machine
- low rank
- total variation
- regularization parameter
- online algorithms
- multiple kernel learning
- image processing
- missing data
- denoising
- convergence rate
- linear combination
- optical flow
- decision trees