Tax risk behavior causes serious loss of fiscal revenue, damages the country's public
infrastructure, and disturbs the market economic order of fair competition. In recent years, tax …

Through extensive experience developing and explaining machine learning (ML)
applications for real-world domains, we have learned that ML models are only as …

The detection of anomalies in time series data is a critical task with many monitoring
applications. Existing systems often fail to encompass an end-to-end detection process, to …

Experts in racket sports like tennis and badminton use tactical analysis to gain insight into
competitors' playing styles. Many data-driven methods apply pattern mining to racket sports …

Abstract The field of Deep Visual Analytics (DVA) has recently arisen from the idea of
developing Visual Interactive Systems supported by deep learning, in order to provide them …

Technology, especially the smartphone, is villainized for taking meaning and time away from
in-person interactions and secluding people into “digital bubbles”. We believe this is not an …

Detecting rare events is essential in various fields, eg, in cyber security or maintenance.
Often, human experts are supported by anomaly detection systems as continuously …

Anomalies are often indicators of malfunction or inefficiency in various systems such as
manufacturing, healthcare, finance, surveillance, to name a few. While the literature is …

With the recent proliferation of temporal observation data comes an increasing demand for
time series anomaly detection. New methods to detect anomalies using machine learning …

Satellite telemetry data is a special case of multivariate time series characterized by large
volumes (in terms of both the number of series and samples), varying sampling rates …