Session Chair: Donato Malerba
| 10:30-10:40 | Detecting Anomalies with LatentOut: Novel Scores, Architectures, and Settings | Fabrizio Angiulli, Fabio Fassetti and Luca Ferragina |
| 10:40-11:00 | Richness Fallacy | Mieczysław Kłopotek and Robert Kłopotek |
| 11:00-11:20 | Adapting loss functions to learning progress improves accuracy of classification in neural networks | Andreas Knoblauch |
| 11:20-11:40 | Multiscale and multivariate time series clustering: A new approach | Jannai Tokotoko, Rodrigue Govan, Hugues Lemonnier and Nazha Selmaoui-Folcher |
| 11:40-12:00 | Improve Calibration Robustness of Temperature Scaling by Penalizing Output Entropy | Jun Zhang, Wen Yao, Xiaoqian Chen and Ling Feng |
| 12:00-12:20 | Understanding Negative Calibration from Entropy Perspective | Jun Zhang, Wen Yao, Xiaoqian Chen and Ling Feng |
| 12:20-12:35 | A New Clustering Preserving Transformation for $k$-Means Algorithm Output | Mieczysław Kłopotek |