Anomaly detection by robust statistics
Real data often contain anomalous cases, also known as outliers. These may spoil the
resulting analysis but they may also contain valuable information. In either case, the ability to …
resulting analysis but they may also contain valuable information. In either case, the ability to …
Adversarial attack and defense strategies of speaker recognition systems: A survey
Speaker recognition is a task that identifies the speaker from multiple audios. Recently,
advances in deep learning have considerably boosted the development of speech signal …
advances in deep learning have considerably boosted the development of speech signal …
Detection of word adversarial examples in text classification: Benchmark and baseline via robust density estimation
Word-level adversarial attacks have shown success in NLP models, drastically decreasing
the performance of transformer-based models in recent years. As a countermeasure …
the performance of transformer-based models in recent years. As a countermeasure …
A fuzzy logic-based approach for fault diagnosis and condition monitoring of industry 4.0 manufacturing processes
Since the introduction of the industry 4.0 paradigm, manufacturing companies are investing
in the development of algorithmic diagnostic solutions for their industrial equipment, relying …
in the development of algorithmic diagnostic solutions for their industrial equipment, relying …
Telemedicine acceptance during the COVID-19 pandemic: an empirical example of robust consistent partial least squares path modeling
The explanation of behaviors concerning telemedicine acceptance is an evolving area of
study. This topic is currently more critical than ever, given that the COVID-19 pandemic is …
study. This topic is currently more critical than ever, given that the COVID-19 pandemic is …
Comparison of new anomaly detection technique for wind turbine condition monitoring using gearbox SCADA data
Anomaly detection for wind turbine condition monitoring is an active area of research within
the wind energy operations and maintenance (O & M) community. In this paper three models …
the wind energy operations and maintenance (O & M) community. In this paper three models …
Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W
Data-driven, or machine learning (ML), approaches have become viable alternatives to
semiempirical methods to construct interatomic potentials, due to their capacity to accurately …
semiempirical methods to construct interatomic potentials, due to their capacity to accurately …
The cellwise minimum covariance determinant estimator
Abstract The usual Minimum Covariance Determinant (MCD) estimator of a covariance
matrix is robust against casewise outliers. These are cases (that is, rows of the data matrix) …
matrix is robust against casewise outliers. These are cases (that is, rows of the data matrix) …
Structural health monitoring under environmental and operational variations using MCD prediction error
This paper proposes a novel technique that aims at detecting the effect of damage on
structural frequency signals as “bad” outliers. To this end, a procedure is developed based …
structural frequency signals as “bad” outliers. To this end, a procedure is developed based …
Constraining the Milky Way Mass Profile with Phase-space Distribution of Satellite Galaxies
Abstract We estimate the Milky Way (MW) halo properties using satellite kinematic data
including the latest measurements from Gaia DR2. With a simulation-based 6D phase-space …
including the latest measurements from Gaia DR2. With a simulation-based 6D phase-space …