14 citations · 26 across the 4 of their papers we have counts for
4 papers
MS-LSTM: Exploring Spatiotemporal Multiscale Representations in Video Prediction Domain
Zhifeng Ma, Hao Zhang, Jie Liu
The drastic variation of motion in spatial and temporal dimensions makes the video prediction task extremely challenging. Existing RNN models obtain higher performance by deepening…
CC-FedAvg: Computationally Customized Federated Averaging
Hao Zhang, Tingting Wu, Siyao Cheng +1
Federated learning (FL) is an emerging paradigm to train model with distributed data from numerous Internet of Things (IoT) devices. It inherently assumes a uniform capacity among…
MS-RNN: A Flexible Multi-Scale Framework for Spatiotemporal Predictive Learning
Zhifeng Ma, Hao Zhang, Jie Liu
Spatiotemporal predictive learning, which predicts future frames through historical prior knowledge with the aid of deep learning, is widely used in many fields. Previous work esse…
FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement
Hao Zhang, Tingting Wu, Siyao Cheng +1
As an emerging technology, federated learning (FL) involves training machine learning models over distributed edge devices, which attracts sustained attention and has been extensiv…