Today's competition between the professional eSports teams is so strong that in-depth
analysis of players' performance literally crucial for creating a powerful team. There are two …

Fraud causes substantial costs and losses for companies and clients in the finance and
insurance industries. Examples are fraudulent credit card transactions or fraudulent claims. It …

The problem of constructing predictive models for early warning systems for diagnostic
maintenance in the aerospace industry is considered. A new approach to predicting rare …

Data from current gravitational wave detectors contains a high rate of transient noise
(glitches) that can trigger false detections and obscure true astrophysical events. Existing …

The goal of anomaly detection is to identify observations that are generated by a distribution
that differs from the reference distribution that qualifies normal behavior. When examining a …

By now, most outlier-detection algorithms struggle to accurately detect both point anomalies
and cluster anomalies simultaneously. Furthermore, a few K-nearest-neighbor-based …

We construct a classification model, that predicts if an earthquake with the magnitude above
a threshold will take place at a given location in a time range 30–180 days from now. A …

In this paper, we consider a problem of failure prediction in the context of predictive
maintenance applications. We present a new approach for rare failures prediction, based on …

Cyber-physical systems (CPSs) use learning-enabled components (LECs) extensively to
cope with various complex tasks under high-uncertainty environments. However, the dataset …

We introduce an anomaly detection method for multivariate time series data with the aim of
identifying critical periods and features influencing extreme climate events like snowmelt in …