63 citations · 120 across the 12 of their papers we have counts for
6 papers · 1 filter
Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks
Jing Ma, Qiuchen Zhang, Jian Lou +3
Tensor factorization has been proved as an efficient unsupervised learning approach for health data analysis, especially for computational phenotyping, where the high-dimensional E…
Temporal Network Embedding via Tensor Factorization
Jing Ma, Qiuchen Zhang, Jian Lou +2
Representation learning on static graph-structured data has shown a significant impact on many real-world applications. However, less attention has been paid to the evolving nature…
SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling
Haowen Lin, Jian Lou, Li Xiong +1
Federated learning enables multiple clients, such as mobile phones and organizations, to collaboratively learn a shared model for prediction while protecting local data privacy. Ho…
Classification Auto-Encoder based Detector against Diverse Data Poisoning Attacks
Fereshteh Razmi, Li Xiong
Poisoning attacks are a category of adversarial machine learning threats in which an adversary attempts to subvert the outcome of the machine learning systems by injecting crafted…
RobustFed: A Truth Inference Approach for Robust Federated Learning
Farnaz Tahmasebian, Jian Lou, Li Xiong
Federated learning is a prominent framework that enables clients (e.g., mobile devices or organizations) to train a collaboratively global model under a central server's orchestrat…
Federated Graph Classification over Non-IID Graphs
Han Xie, Jing Ma, Li Xiong +1
Federated learning has emerged as an important paradigm for training machine learning models in different domains. For graph-level tasks such as graph classification, graphs can al…