Experiments on a Parallel Nonlinear Jacobi-Davidson Algorithm. - Yoichi Matsuo; Hua Guo; Peter Arbenz (ICCS, 2014)

Workflow extraction for service operation using multiple unstructured trouble tickets. - Akio Watanabe; Keisuke Ishibashi; Tsuyoshi Toyono; Tatsuaki Kimura; Keishiro Watanabe; Yoichi Matsuo; Kohei Shiomoto (NOMS, 2016)

Root-Cause Diagnosis for Rare Failures Using Bayesian Network with Dynamic Modification. - Yoichi Matsuo; Yuusuke Nakano; Akio Watanabe; Keishiro Watanabe; Keisuke Ishibashi; Ryoichi Kawahara (ICC, 2018)

Workflow Extraction for Service Operation Using Multiple Unstructured Trouble Tickets. - Akio Watanabe; Keisuke Ishibashi; Tsuyoshi Toyono; Keishiro Watanabe; Tatsuaki Kimura; Yoichi Matsuo; Kohei Shiomoto; Ryoichi Kawahara (IEICE Trans. Inf. Syst., 2018)

A Framework for Automatic Failure Recovery in ICT Systems by Deep Reinforcement Learning. - Hiroki Ikeuchi; Jiawen Ge; Yoichi Matsuo; Keishiro Watanabe (ICDCS, 2020)

Recovery command generation towards automatic recovery in ICT systems by Seq2Seq learning. - Hiroki Ikeuchi; Akio Watanabe; Tsutomu Hirao; Makoto Morishita; Masaaki Nishino; Yoichi Matsuo; Keishiro Watanabe (NOMS, 2020)

Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise. - Yuka Hashimoto; Isao Ishikawa; Masahiro Ikeda; Yoichi Matsuo; Yoshinobu Kawahara (J. Mach. Learn. Res., 2020)

Performance Analysis of Anomaly Detection Methods for Application System on Kubernetes with Auto-scaling and Self-healing. - Yoichi Matsuo; Daisuke Ikegami (CNSM, 2021)

Fault Detection of ICT systems with Deep Learning Model for Missing Data. - Kengo Tajiri; Tomoharu Iwata; Yoichi Matsuo; Keishiro Watanabe (IM, 2021)

Shapley-value-based Quality Degradation Analysis Method for Adaptive Bitrate Streaming Services. - Yoichi Matsuo; Kazuhisa Yamagishi; Shoko Takahashi (MMSP, 2021)

DeepSIP: A System for Predicting Service Impact of Network Failure by Temporal Multimodal CNN. - Yoichi Matsuo; Tatsuaki Kimura; Ken Nishimatsu (IEICE Trans. Commun., 2021)

Empirical Analysis of the Fine-Tuning for Unsupervised Anomaly Detection in the ICT System. - Yoichi Matsuo (CNSM, 2023)

CMRCV: Causal Modeling to Localize Failed Equipment by Representative Nodes and Contribution Values. - Yoichi Matsuo; Yuusuke Nakano; Keishiro Watanabe (ICNC, 2023)

Integrating state prediction into the Deep Reinforcement Learning for the Autoscaling of Core Network Functions. - Yoichi Matsuo; Jatinder Singh; Shantanu Verma; Guillaume Fraysse (NOMS, 2023)

Autoscaling Packet Core Network Functions with Deep Reinforcement Learning. - Jatinder Singh; Shantanu Verma; Yoichi Matsuo; Francesca Fossati; Guillaume Fraysse (NOMS, 2023)

Optimizing Edge-Cloud Cooperation for Machine Learning Accuracy Considering Transmission Latency and Bandwidth Congestion. - Kengo Tajiri; Ryoichi Kawahara; Yoichi Matsuo (IEICE Trans. Commun., 2023)

Adversarial Deep Domain Adaptation Method for Unsupervised Anomaly Detection. - Yoichi Matsuo; Kengo Tajiri (6GNet, 2024)

Improving Fault Device Identification Method using Alarm Clustering Approach. - Yoichi Matsuo; Yuichi Suto; Yusuke Makino; Kazumich Sato (CNSM, 2024)

Vehicle Traffic Density Estimation with Deep Learning for Predicting Communication Traffic Volume by Vehicle Communication Services. - Yoshie Morita; Kengo Tajiri; Yoichi Matsuo (VTC Fall, 2024)