2022_09_08_Anomaly and Change Point Detection

Kaiserslautern, Workshop / September 08, 2022 - September 09, 2022

Anomaly and Change Point Detection

Are you interested in the topics of »Anomaly and Change Point Detection« or are you already working in the field and looking for an opportunity to exchange and discuss? Then this workshop is just right for you!

Our department »Financial Mathematics« organizes in cooperation with the German Research Center for Artificial Intelligence (DFKI) a workshop on »Anomaly and Change Point Detection«. Here you have the opportunity to present questions and first research results from the fields of anomaly change point detection in talks or posters.

Event details

Program

Program for download

Drinks and snacks will be offered during the coffee breaks. There will also be a dinner afterwards. The costs for the dinner are to be borne by the participants themselves.

Registration

To register, please use the form in the blue teaser box.

Location

The workshop will take place in Kaiserslautern. It is planned to organize a part of the event at Fraunhofer ITWM and a part at the premises of DFKI. More detailed information will follow as soon as the detailed program is available.

Date

September 08, 2022 - September 09, 2022

Download this event as iCal

Language

English

Planned Topics in the Workshop Program

The topics of »Anomaly and Change Point Detection« are becoming more and more important. In the current development, more and more data is available, not least with regard to Germany's digitization initiative. This enables the use of Machine Learning (ML) methods and their further development in more and more areas.

At the same time, errors and changes are integrated in the data, which we would like to detect and use. Here, many research questions are still open. This workshop aims to provide a platform for exchange and discussion.

The research areas of »Anomaly and Change Point Detection« cover many different fields and are used in applications to answer a wide variety of questions. As an example, the following topics are mentioned here (other topics are conceivable):

Anomaly Detection
Change Point Detection
Outlier Detection
Unsupervised Machine Learning (ML)
Data Analysis
Mixed Type Datasets (e.g., tabular data with categorical and numerical columns)
Dataset Comparison
Dataset Similarity
Transferability of Results to Internal Datasets
Dataset Generation
Data Synthesis
Explainability

Examples of Fields of Application in »Anomaly and Change Point Detection«

The topics of »Anomaly and Change Point Detection« are also becoming more and more important in various areas in practice. This is because more and more data is available due to current developments, not least with regard to Germany's digitalisation initiative. This enables the use of machine learning (ML) methods and their further development. The detection of anomalies or outliers always means discovering patterns in data that are not expected and cannot be classified in a defined normal state.

Well-known examples from the application and practice of »Anomaly and Change Point Detection« include:

In production: In the manufacturing industry, anomaly detection is important for improving quality control, for example. A distinction is often made between one-off errors (anomaly) or general misadjustments of the machine (change point/structure break). Then, for example, the sensors can be adjusted.
With climate change in general, outliers in the data occure frequently and the real change detectable in the general trend. However, an example from the past also shows exceptions. In the case of the ozone measurement in the 1980s: The ozone hole had already been discovered before, but was deleted from the data as an anomaly. The data was therefore misinterpreted.
Parking data during the Corona pandemic: When predicting parking availability, major events are often the outliers, as here, for example, on a Sunday, there are suddenly hardly any spaces available, whereas at Corona the general parking situation was minimised, as fewer people were on the road at all.
In the large area of financial data, anomaly detection is versatile. It can be used to identify fraud or manipulation in the network, but also to detect minor changes in the usage behaviour of customers and thus better predict their behaviour.

Workshop

Kaiserslautern, Workshop / September 08, 2022 - September 09, 2022

Anomaly and Change Point Detection

Registration and Call For Presentations

Event details

Program

Registration

Location

Language

Planned Topics in the Workshop Program

Further Information

Examples of Fields of Application in »Anomaly and Change Point Detection«

Contact Press / Media

Dr. Stefanie Schwaar

Contact Press / Media

Dr. Jörn Hees

Contact Press / Media

Sabrina Klar