ArchiveDMC Program
Current EEST (UTC+3) date and time:
| 16:00-18:00 EEST | Monday 05.09.2022 on-site. Chairs: Andrzej Janusz, Michał Okulewicz, Dominik Ślęzak JOIN HERE |
| 16:00-16:20 | Michał Okulewicz, Predicting the Costs of Forwarding Contracts: Analysis of Data Mining Competition Results |
| 16:20-16:40 | Andrzej Janusz, Dominik Ślęzak, KnowledgePit Meets BrightBox: A Step Toward Insightful Investigation of the Results of Data Mining Competitions |
| 16:40-17:00 | Dymitr Ruta, Ming Liu, Ling Cen, Quang Hieu Vu - Diversified gradient boosting ensembles for prediction of the cost of forwarding contracts |
| 17:00-17:20 | Podlodowski Łukasz, Predicting the Costs of Forwarding Contracts Using XGBoost and a Deep Neural Network |
| 17:20-17:40 | Eftim Zdravevski, Application of Diversified Ensemble Learning in Real-life Business Problems: The Case of Predicting Costs of Forwarding Contracts |
| 17:40-18:00 | Sławomir Pioroński, Tomasz Górecki, Using gradient boosting trees to predict the costs of forwarding contracts |
| 09:00-11:00 EEST | Wednesday 07.09.2022 online. Chairs: Andrzej Janusz, Michał Okulewicz, Dominik Ślęzak, Marcin Szczuka JOIN HERE |
| 09:00-09:20 | Haitao Xiao, Yuling Liu, Dan Du, Zhigang Lu - An Approach for Predicting the Costs of Forwarding Contracts using Gradient Boosting |
| 09:20-09:40 | Quang Hieu Vu, Ling Cen, Dymitr Ruta, Ming Liu - Key Factors to Consider when Predicting the Costs of Forwarding Contracts |
| 09:40-10:00 | Aleksandra Lewandowska - XGBoost meets TabNet in Predicting the Costs of Forwarding Contracts |
| 10:00-10:20 | Eyad Kannout, Michał Grodzki, Marek Grzegorowski - Considering various aspects of models’ quality in the ML pipeline - application in the logistics sector |
| 10:20-10:40 | Stanisław Kaźmierczak - Prediction of the Costs of Forwarding Contracts with Machine Learning Methods |
| 10:40-11:00 | Marcin Szczuka, Andrzej Janusz, Andrzej Bukała, Bogusław Cyganek, Jakub Grabek, Łukasz Przebinda, Dominik Ślęzak, Tomasz Tajmajer, Andżelika Zalewska - What’s next at KnowledgePit: Privacy-preserving Matching of Encrypted Images (IEEE BigData 2022 Cup) |
