Fetching the paper…
Reading the bibliography…
We develop simple differentially private optimization algorithms that move along directions of (expected) descent to find an approximate second-order solution for nonconvex ERM.
Topics in Random Matrix Theory
T. Tao · 2012
Earlier work this paper cites.
The Algorithmic Foundations of Differential Privacy
C. Dwork and A. Roth · 2014
Earlier work this paper cites.
Understanding Machine Learning: From Theory to Algorithms
S. Shalev-Shwartz and S. Ben-David · 2014
Earlier work this paper cites.
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
M. Bun and T. Steinke · 2016
Earlier work this paper cites.
Accelerated Methods for Non-Convex Optimization, Feb. 2017
Y. Carmon, J. C. Duchi, O. Hinder, and A. Sidford · 2017
Earlier work this paper cites.
Sub-sampled Cubic Regularization for Non-convex Optimization
J. M. Kohler and A. Lucchi · 2017
Cited alongside, same era.
Renyi Differential Privacy
I. Mironov · 2017
Cited alongside, same era.
Efficient Private ERM for Smooth Objectives
J. Zhang, K. Zheng, W. Mou, and L. Wang · 2017
Cited alongside, same era.
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences, Nov. 2018
B. Balle, G. Barthe, and M. Gaboardi · 2018
Cited alongside, same era.
High-Dimensional Probability: An Introduction with Applications in Data Science
R. Vershynin · 2018
Cited alongside, same era.
Differentially Private Empirical Risk Minimization Revisited: Faster and More General
D. Wang, M. Ye, and J. Xu
Cited in the paper.
Subsampled R\’enyi Differential Privacy and Analytical Moments Accountant
Y.-X. Wang, B. Balle, and S. Kasiviswanathan
Cited in the paper.
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View
D. Wang and J. Xu · 2019
Later among the works it cites.
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions
D. Wang, C. Chen, and J. Xu · 2019
Later among the works it cites.
Stochastic Adaptive Line Search for Differentially Private Optimization
C. Chen and J. Lee · 2020
Later among the works it cites.
Escaping Saddle Points of Empirical Risk Privately and Scalably via DP-Trust Region Method
D. Wang and J. Xu · 2021
Later among the works it cites.
Optimization for Data Analysis
S. J. Wright and B. Recht · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…