62 citations · 107 across the 24 of their papers we have counts for
8 papers · 1 filter
Detection of Global Anomalies on Distributed IoT Edges with Device-to-Device Communication
Hideya Ochiai, Riku Nishihata, Eisuke Tomiyama +2
Anomaly detection is an important function in IoT applications for finding outliers caused by abnormal events. Anomaly detection sometimes comes with high-frequency data sampling w…
Associative Transformer
Yuwei Sun, Hideya Ochiai, Zhirong Wu +2
Emerging from the pairwise attention in conventional Transformers, there is a growing interest in sparse attention mechanisms that align more closely with localized, contextual lea…
Resilience of Wireless Ad Hoc Federated Learning against Model Poisoning Attacks
Naoya Tezuka, Hideya Ochiai, Yuwei Sun +1
Wireless ad hoc federated learning (WAFL) is a fully decentralized collaborative machine learning framework organized by opportunistically encountered mobile nodes. Compared to con…
Wireless Ad Hoc Federated Learning: A Fully Distributed Cooperative Machine Learning
Hideya Ochiai, Yuwei Sun, Qingzhe Jin +2
Privacy-sensitive data is stored in autonomous vehicles, smart devices, or sensor nodes that can move around with making opportunistic contact with each other. Federation among suc…
Feature Distribution Matching for Federated Domain Generalization
Yuwei Sun, Ng Chong, Hideya Ochiai
Multi-source domain adaptation has been intensively studied. The distribution shift in features inherent to specific domains causes the negative transfer problem, degrading a model…
Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis
Yuwei Sun, Hideya Ochiai, Jun Sakuma
Model poisoning attacks on federated learning (FL) intrude in the entire system via compromising an edge model, resulting in malfunctioning of machine learning models. Such comprom…
Homogeneous Learning: Self-Attention Decentralized Deep Learning
Yuwei Sun, Hideya Ochiai
Federated learning (FL) has been facilitating privacy-preserving deep learning in many walks of life such as medical image classification, network intrusion detection, and so forth…
Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks
Yuwei Sun, Ng Chong, Hideya Ochiai
An attack on deep learning systems where intelligent machines collaborate to solve problems could cause a node in the network to make a mistake on a critical judgment. At the same…