Search Results for author: Keishiro Watanabe

Found 4 papers, 0 papers with code

Dividing Deep Learning Model for Continuous Anomaly Detection of Inconsistent ICT Systems

no code implementations24 Mar 2020 Kengo Tajiri, Yasuhiro Ikeda, Yuusuke Nakano, Keishiro Watanabe

We present the results from experiments involving benchmark data and real log data, which indicate that our method using divided models does not decrease anomaly detection accuracy and a model for anomaly detection can be divided to continue monitoring a network state even if some the log data change.

Anomaly Detection

Recovery command generation towards automatic recovery in ICT systems by Seq2Seq learning

no code implementations24 Mar 2020 Hiroki Ikeuchi, Akio Watanabe, Tsutomu Hirao, Makoto Morishita, Masaaki Nishino, Yoichi Matsuo, Keishiro Watanabe

With the increase in scale and complexity of ICT systems, their operation increasingly requires automatic recovery from failures.

Anomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization

no code implementations18 Dec 2018 Yasuhiro Ikeda, Keisuke Ishibashi, Yuusuke Nakano, Keishiro Watanabe, Ryoichi Kawahara

Automated anomaly detection is essential for managing information and communications technology (ICT) systems to maintain reliable services with minimum burden on operators.

Anomaly Detection

Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders

no code implementations12 Nov 2018 Yasuhiro Ikeda, Kengo Tajiri, Yuusuke Nakano, Keishiro Watanabe, Keisuke Ishibashi

Our algorithm is based on an approximative probabilistic model that considers the existence of anomalies in the data, and by maximizing the log-likelihood, we estimate which dimensions contribute to determining data as an anomaly.

Anomaly Detection Dimensionality Reduction

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