Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Efficient Private ERM for Smooth Objectives
Differentially Private Empirical Risk Minimization
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences
Nearly Optimal Private LASSO
Communication Efficient Coresets for Empirical Loss Minimization
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification
Empirical Risk Minimization under Fairness Constraints
A Practical Approach to Differential Private Learning
Fast Rates for Empirical Risk Minimization of Strict Saddle Problems
Model-Agnostic Private Learning
Differentially private data aggregation with optimal utility
Differentially Private Bayesian Learning on Distributed Data
Stochastic Gradient Descent with Differentially Private Updates
Differentially Private Random Decision Forests using Smooth Sensitivity
EXpectation Propagation LOgistic REgRession (EXPLORER): distributed privacy-preserving online model learning.
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences
Tight Complexity Bounds for Optimizing Composite Objectives
Privacy-Preserving Logistic Regression
Smooth sensitivity and sampling in private data analysis
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
extramedullary waldenstrom macroglobulinemia .
Information Retrieval Applications in Software Maintenance and Evolution
An empirical investigation of socio-technical code review metrics and security vulnerabilities