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20222025
most citedUnsupervised Deep Learning for IoT Time Series

67 citations · 134 across the 14 of their papers we have counts for

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Showing cs.LGShow all

8 papers · 1 filter

cs.LG202510 cited

Anomaly Detection in Event-triggered Traffic Time Series via Similarity Learning

Shaoyu Dou, Kai Yang, Yang Jiao +2

Time series analysis has achieved great success in cyber security such as intrusion detection and device identification. Learning similarities among multiple time series is a cruci…

cs.LG20253 cited

Robust Group Anomaly Detection for Quasi-Periodic Network Time Series

Kai Yang, Shaoyu Dou, Pan Luo +2

Many real-world multivariate time series are collected from a network of physical objects embedded with software, electronics, and sensors. The quasi-periodic signals generated by…

cs.LG202510 cited

Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning

Hui Ma, Kai Yang, Yang Jiao

Network traffic prediction plays a crucial role in intelligent network operation. Traditional prediction methods often rely on centralized training, necessitating the transfer of v…

cs.LG2025

Argus: Federated Non-convex Bilevel Learning over 6G Space-Air-Ground Integrated Network

Ya Liu, Kai Yang, Yu Zhu +2

The space-air-ground integrated network (SAGIN) has recently emerged as a core element in the 6G networks. However, traditional centralized and synchronous optimization algorithms…

cs.LG2024

Provably Convergent Federated Trilevel Learning

Yang Jiao, Kai Yang, Tiancheng Wu +2

Trilevel learning, also called trilevel optimization (TLO), has been recognized as a powerful modelling tool for hierarchical decision process and widely applied in many machine le…

cs.LG2023

Bayesian Beta-Bernoulli Process Sparse Coding with Deep Neural Networks

Arunesh Mittal, Kai Yang, Paul Sajda +1

Several approximate inference methods have been proposed for deep discrete latent variable models. However, non-parametric methods which have previously been successfully employed…