12 citations · 62 across the 39 of their papers we have counts for
6 papers · 1 filter
Balanced Multi-modal Federated Learning via Cross-Modal Infiltration
Yunfeng Fan, Wenchao Xu, Haozhao Wang +2
Federated learning (FL) underpins advancements in privacy-preserving distributed computing by collaboratively training neural networks without exposing clients' raw data. Current F…
Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence
Xin Yuan, Ning Li, kang Wei +4
The edge intelligence (EI) has been widely applied recently. Spliting the model between device, edge server, and cloud can improve the performance of EI greatly. The model segmenta…
MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition
Jingcai Guo, Yuanyuan Xu, Wenchao Xu +3
Malware open-set recognition (MOSR) aims at jointly classifying malware samples from known families and detect the ones from novel unknown families, respectively. Existing works mo…
Towards Unbiased Training in Federated Open-world Semi-supervised Learning
Jie Zhang, Xiaosong Ma, Song Guo +1
Federated Semi-supervised Learning (FedSSL) has emerged as a new paradigm for allowing distributed clients to collaboratively train a machine learning model over scarce labeled dat…
DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning
Yunfeng Fan, Wenchao Xu, Haozhao Wang +3
Online Class-Incremental (OCI) learning has sparked new approaches to expand the previously trained model knowledge from sequentially arriving data streams with new classes. Unfort…
Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement
Fushuo Huo, Wenchao Xu, Jingcai Guo +3
This paper investigates a new, practical, but challenging problem named Non-exemplar Online Class-incremental continual Learning (NO-CL), which aims to preserve the discernibility…