Lu Lin

Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization

2021 · arXiv (Cornell University)

Due to the explosion in the size of the training datasets, distributed learning has received growing interest in recent years. One of the major bottlenecks is the large communication cost between the central server and …

Communication-Efficient Adaptive Federated Learning

2022 · arXiv (Cornell University)

Federated learning is a machine learning training paradigm that enables clients to jointly train models without sharing their own localized data. However, the implementation of federated learning in practice still faces numerous challenges, such as …

How Powerful is Implicit Denoising in Graph Neural Networks

2022 · arXiv (Cornell University)

Graph Neural Networks (GNNs), which aggregate features from neighbors, are widely used for graph-structured data processing due to their powerful representation learning capabilities. It is generally believed that GNNs can implicitly remove the non-predictive noises. …

Research on Subjective Question Automatic Scoring Algorithm based on Multi-pattern Matching and Feature Fusion

2023

Aiming at the current Chinese subjective question automatic scoring technology mostly adopts simple ways such as feature fusion or similarity combination calculation, which leads to large error in subjective question score judgement and low practicality, …