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09/20/2023
Face Aging via Diffusion-based Editing
In this paper, we address the problem of face aging: generating past or ...
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06/13/2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Current deep neural networks (DNNs) are vulnerable to adversarial attack...
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09/10/2021
Toward Communication Efficient Adaptive Gradient Method
In recent years, distributed optimization is proven to be an effective a...
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06/25/2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Providing privacy protection has been one of the primary motivations of ...
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06/27/2020
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
Deep learning models are increasingly popular in many machine learning a...
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06/24/2020
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds
We study differentially private (DP) algorithms for stochastic non-conve...
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10/15/2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
The adaptive momentum method (AdaMM), which uses past gradients to updat...
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09/30/2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML
In this paper, we study the problem of constrained robust (min-max) opti...
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06/04/2019
Distributed Training with Heterogeneous Data: Bridging Median and Mean Based Algorithms
Recently, there is a growing interest in the study of median-based algor...
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08/08/2018