1 citations · 2 across the 2 of their papers we have counts for
7 papers
Data Poisoning Attacks and Defenses to Crowdsourcing Systems
Minghong Fang, Minghao Sun, Qi Li +3
A key challenge of big data analytics is how to collect a large volume of (labeled) data. Crowdsourcing aims to address this challenge via aggregating and estimating high-quality d…
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
Federated learning (FL) is a distributed machine learning architecture that leverages a large number of workers to jointly learn a model with decentralized data. FL has received in…
Toward Low-Cost and Stable Blockchain Networks
Minghong Fang, Jia Liu
Envisioned to be the future of secured distributed systems, blockchain networks have received increasing attention from both the industry and academia in recent years. However, blo…
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems
Minghong Fang, Neil Zhenqiang Gong, Jia Liu
Recommender system is an essential component of web services to engage users. Popular recommender systems model user preferences and item properties using a large amount of crowdso…
Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach
Xin Zhang, Minghong Fang, Jia Liu +1
With rise of machine learning (ML) and the proliferation of smart mobile devices, recent years have witnessed a surge of interest in performing ML in wireless edge networks. In thi…
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach
Haibo Yang, Xin Zhang, Minghong Fang +1
In this work, we consider the resilience of distributed algorithms based on stochastic gradient descent (SGD) in distributed learning with potentially Byzantine attackers, who coul…