6 papers
FedTaste: Topology-Aware Structural Transfer for Multimodal Federated Learning with Missing Modalities
Haochen Liang, Jie Zhang, Hideya Ochiai
Multimodal Federated Learning is often challenged by arbitrary modality missingness and Non-IID data distributions, which lead to severe representation drift and hinder effective c…
Detection of Anomalous Network Nodes via Hierarchical Prediction and Extreme Value Theory
Sevvandi Kandanaarachchi, Mahdi Abolghasemi, Hideya Ochiai +2
Continuously evolving cyber-attacks against industrial networks reduce the effectiveness of signature-based detection methods. Once malware has infiltrated a network (for example,…
FedDetox: Robust Federated SLM Alignment via On-Device Data Sanitization
Shunan Zhu, Jiawei Chen, Yonghao Yu +1
As high quality public data becomes scarce, Federated Learning (FL) provides a vital pathway to leverage valuable private user data while preserving privacy. However, real-world cl…
NeuroSCA: Neuro-Symbolic Constraint Abstraction for Smart Contract Hybrid Fuzzing
Haochen Liang, Jiawei Chen, Hideya Ochiai
Hybrid fuzzing combines greybox fuzzing's throughput with the precision of symbolic execution to uncover deep smart contract vulnerabilities. However, its effectiveness is often li…
University Building Recognition Dataset in Thailand for the mission-oriented IoT sensor system
Takara Taniguchi, Yudai Ueda, Atsuya Muramatsu +4
Many industrial sectors have been using of machine learning at inference mode on edge devices. Future directions show that training on edge devices is promising due to improvements…
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…