research
∙
08/25/2023
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction
Despite the recent success of Graph Neural Networks (GNNs), it remains c...
share
research
∙
05/31/2022
Distributed Graph Neural Network Training with Periodic Historical Embedding Synchronization
Despite the recent success of Graph Neural Networks (GNNs), it remains c...
research
∙
09/17/2021
LOF: Structure-Aware Line Tracking based on Optical Flow
Lines provide the significantly richer geometric structural information ...
research
∙
09/01/2021
Asynchronous Federated Learning for Sensor Data with Concept Drift
Federated learning (FL) involves multiple distributed devices jointly tr...
research
∙
08/10/2021
Method Towards CVPR 2021 SimLocMatch Challenge
This report describes Megvii-3D team's approach towards SimLocMatch Chal...
research
∙
08/10/2021
Method Towards CVPR 2021 Image Matching Challenge
This report describes Megvii-3D team's approach towards CVPR 2021 Image ...
research
∙
05/20/2021
Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework
The Graph Augmented Multi-layer Perceptron (GA-MLP) model is an attracti...
research
∙
10/12/2020
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Federated learning (FL) involves training a model over massive distribut...
research
∙
09/09/2020
Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training
Alternating minimization methods have recently been proposed as alternat...
research
∙
01/25/2020
TiFL: A Tier-based Federated Learning System
Federated Learning (FL) enables learning a shared model across many clie...
research
∙
05/13/2019
Federated Multi-task Hierarchical Attention Model for Sensor Analytics
Sensors are an integral part of modern Internet of Things (IoT) applicat...
research
∙
08/08/2018
