177 citations · 631 across the 42 of their papers we have counts for
7 papers · 1 filter
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…
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…
GestureGPT: Toward Zero-Shot Free-Form Hand Gesture Understanding with Large Language Model Agents
Xin Zeng, Xiaoyu Wang, Tengxiang Zhang +3
Existing gesture interfaces only work with a fixed set of gestures defined either by interface designers or by users themselves, which introduces learning or demonstration efforts…
A Knowledge-Driven Cross-view Contrastive Learning for EEG Representation
Weining Weng, Yang Gu, Qihui Zhang +3
Due to the abundant neurophysiological information in the electroencephalogram (EEG) signal, EEG signals integrated with deep learning methods have gained substantial traction acro…
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…
FedBone: Towards Large-Scale Federated Multi-Task Learning
Yiqiang Chen, Teng Zhang, Xinlong Jiang +3
Heterogeneous federated multi-task learning (HFMTL) is a federated learning technique that combines heterogeneous tasks of different clients to achieve more accurate, comprehensive…
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…