research
∙
02/17/2023
Privately Customizing Prefinetuning to Better Match User Data in Federated Learning
In Federated Learning (FL), accessing private client data incurs communi...
share
research
∙
04/04/2022
FedSynth: Gradient Compression via Synthetic Data in Federated Learning
Model compression is important in federated learning (FL) with large mod...
research
∙
11/08/2021
Papaya: Practical, Private, and Scalable Federated Learning
Cross-device Federated Learning (FL) is a distributed learning paradigm ...
research
∙
08/22/2021
Convex Latent Effect Logit Model via Sparse and Low-rank Decomposition
In this paper, we propose a convex formulation for learning logistic reg...
research
∙
06/11/2021
Federated Learning with Buffered Asynchronous Aggregation
Federated Learning (FL) trains a shared model across distributed devices...
research
∙
10/28/2019
Evaluating Lottery Tickets Under Distributional Shifts
The Lottery Ticket Hypothesis suggests large, over-parameterized neural ...
research
∙
11/01/2018