activity
20212023
most citedDomain Generalization for Activity Recognition via Adaptive Feature Fusion

3 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

Differentially Private Pre-Trained Model Fusion using Decentralized Federated Graph Matching

Qian Chen, Yiqiang Chen, Xinlong Jiang +5

Model fusion is becoming a crucial component in the context of model-as-a-service scenarios, enabling the delivery of high-quality model services to local users. However, this appr…

cs.AI20231 cited

ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning

Wang Lu, Hao Yu, Jindong Wang +6

When personalized federated learning (FL) meets large foundation models, new challenges arise from various limitations in resources. In addition to typical limitations such as data…

cs.LG20232 cited

DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization

Wang Lu, Jindong Wang, Xinwei Sun +4

Time series remains one of the most challenging modalities in machine learning research. The out-of-distribution (OOD) detection and generalization on time series tend to suffer du…

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.CV20223 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.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…