Track 1: Artificial Intelligence
Data Mining Competition: Network Device Workload Prediction
The AI Track aims at establishing the synergy between FedCSIS technical sessions, which encompass wide range of aspects of Artificial Intelligence. With its longest-tradition threads (such as AAIA and WCO, focusing on AI Applications and Computational Optimization, respectively), this track is also open to new initiatives categorized with respect to both, the emerging AI-related methodologies and practical usage areas. Nowadays, AI is usually perceived as closely related to the data, therefore, this track’s scope includes the elements of Machine Learning, Data Quality, Big Data, etc. However, the domain of Artificial Intelligence is actually far richer and our ultimate goal is to show relationships between all of its subareas, emphasizing a cross-disciplinary nature of the disciplines such as XAI, HCI, and others.
Track 1 Chairs (email email@example.com):
- Ślęzak, Dominik, University of Warsaw, Poland
- Matwin, Stan, Dalhousie University, Canada
Track 1 includes technical sessions: