184 citations · 464 across the 20 of their papers we have counts for
8 papers · 1 filter
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion
Zhouyuan Huo, Khe Chai Sim, Bo Li +3
Self-supervised pre-training of a speech foundation model, followed by supervised fine-tuning, has shown impressive quality improvements on automatic speech recognition (ASR) tasks…
Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning
Peng Ye, Zhifeng Jiang, Wei Wang +2
Federated learning (FL) has increasingly been deployed, in its vertical form, among organizations to facilitate secure collaborative training over siloed data. In vertical FL (VFL)…
Graph Contrastive Learning with Personalized Augmentation
Xin Zhang, Qiaoyu Tan, Xiao Huang +1
Graph contrastive learning (GCL) has emerged as an effective tool for learning unsupervised representations of graphs. The key idea is to maximize the agreement between two augment…
A Comprehensive Survey of Incentive Mechanism for Federated Learning
Rongfei Zeng, Chao Zeng, Xingwei Wang +2
Federated learning utilizes various resources provided by participants to collaboratively train a global model, which potentially address the data privacy issue of machine learning…
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie, Minghao Chen, Pin-Yu Chen +1
Federated Learning (FL) as a distributed learning paradigm that aggregates information from diverse clients to train a shared global model, has demonstrated great success. However,…
Attack-Resistant Federated Learning with Residual-based Reweighting
Shuhao Fu, Chulin Xie, Bo Li +1
Federated learning has a variety of applications in multiple domains by utilizing private training data stored on different devices. However, the aggregation process in federated l…