research
∙
01/10/2022
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
We consider a platform's problem of collecting data from privacy sensiti...
share
research
∙
06/25/2021
Private Adaptive Gradient Methods for Convex Optimization
We study adaptive methods for differentially private convex optimization...
research
∙
02/07/2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks
In this paper, we study the generalization properties of Model-Agnostic ...
research
∙
09/22/2020
Entropic Compressibility of Lévy Processes
In contrast to their seemingly simple and shared structure of independen...
research
∙
02/19/2020
Personalized Federated Learning: A Meta-Learning Approach
The goal of federated learning is to design algorithms in which several ...
research
∙
02/13/2020
An Optimal Multistage Stochastic Gradient Method for Minimax Problems
In this paper, we study the minimax optimization problem in the smooth a...
research
∙
02/12/2020
Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning
We consider Model-Agnostic Meta-Learning (MAML) methods for Reinforcemen...
research
∙
08/27/2019
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
In this paper, we study the convergence theory of a class of gradient-ba...
research
∙
01/23/2019