activity
20192023
most citedCross-domain Activity Recognition via Substructural Optimal Transport

60 citations · 159 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2023

Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning

Xin Qin, Jindong Wang, Shuo Ma +4

Human activity recognition (HAR) is a time series classification task that focuses on identifying the motion patterns from human sensor readings. Adequate data is essential but a m…

cs.CV2022★ 3 cited

Domain Generalization for Activity Recognition via Adaptive Feature Fusion

Xin Qin, Jindong Wang, Yiqiang Chen +2

Human activity recognition requires the efforts to build a generalizable model using the training datasets with the hope to achieve good performance in test datasets. However, in r…

cs.AI2022

Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition

Wang Lu, Jindong Wang, Yiqiang Chen +3

It is expensive and time-consuming to collect sufficient labeled data to build human activity recognition (HAR) models. Training on existing data often makes the model biased towar…

cs.LG2022★ 7 cited

MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

Yiqiang Chen, Wang Lu, Xin Qin +2

Federated learning has attracted increasing attention to building models without accessing the raw user data, especially in healthcare. In real applications, different federations…

cs.LG2021

Personalized Federated Learning with Adaptive Batchnorm for Healthcare

Wang Lu, Jindong Wang, Yiqiang Chen +4

There is a growing interest in applying machine learning techniques to healthcare. Recently, federated learning (FL) is gaining popularity since it allows researchers to train powe…

cs.LG2021★ 5 cited

FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare

Yiqiang Chen, Wang Lu, Jindong Wang +1

The success of machine learning applications often needs a large quantity of data. Recently, federated learning (FL) is attracting increasing attention due to the demand for data p…

eess.SP2021★ 60 cited

Cross-domain Activity Recognition via Substructural Optimal Transport

Wang Lu, Yiqiang Chen, Jindong Wang +1

It is expensive and time-consuming to collect sufficient labeled data for human activity recognition (HAR). Domain adaptation is a promising approach for cross-domain activity reco…

cs.LG2020★ 39 cited

FOCUS: Dealing with Label Quality Disparity in Federated Learning

Yiqiang Chen, Xiaodong Yang, Xin Qin +3

Ubiquitous systems with End-Edge-Cloud architecture are increasingly being used in healthcare applications. Federated Learning (FL) is highly useful for such applications, due to s…

cs.LG2019★ 45 cited

FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare

Yiqiang Chen, Jindong Wang, Chaohui Yu +2

With the rapid development of computing technology, wearable devices such as smart phones and wristbands make it easy to get access to people's health information including activit…