1.9k citations · 2.4k across the 10 of their papers we have counts for
5 papers · 1 filter
Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro +3
We propose a novel federated learning method for distributively training neural network models, where the server orchestrates cooperation between a subset of randomly chosen device…
Intrinsically Motivated Self-supervised Learning in Reinforcement Learning
Yue Zhao, Chenzhuang Du, Hang Zhao +1
In vision-based reinforcement learning (RL) tasks, it is prevalent to assign auxiliary tasks with a surrogate self-supervised loss so as to obtain more semantic representations and…
SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula
Colin Wan, Zheng Li, Alicia Guo +1
Synthetic population generation is the process of combining multiple socioeconomic and demographic datasets from different sources and/or granularity levels, and downscaling them t…
Federated Learning with Non-IID Data
Yue Zhao, Meng Li, Liangzhen Lai +3
Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model for prediction, while keeping the training data…
A Learning-to-Infer Method for Real-Time Power Grid Multi-Line Outage Identification
Yue Zhao, Jianshu Chen, H. Vincent Poor
Identifying a potentially large number of simultaneous line outages in power transmission networks in real time is a computationally hard problem. This is because the number of hyp…