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ORCIDPKDD/ECML 2020: Virtual Event / Ghent, Belgium - Workshops
- Irena Koprinska
, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6
Fifth Workshop on Data Science for Social Good (SoGood 2020)
- Hendrik Santoso Sugiarto, Ee-Peng Lim:
On Modeling Labor Markets for Fine-Grained Insights. 9-25 - Benjamin C. Evans, Allan Tucker, Oliver R. Wearn, Chris Carbone:
Reasoning About Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications. 26-37 - Juan de Benedetti, Namir Oues, Zhenchen Wang, Puja Myles, Allan Tucker:
Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks. 38-47 - Seyed Erfan Sajjadi, Barbara Draghi, Lucia Sacchi, Arianna Dagliati, John H. Holmes, Allan Tucker:
Building Trajectories Over Topology with TDA-PTS: An Application in Modelling Temporal Phenotypes of Disease. 48-61 - Jatin Bedi, Durga Toshniwal:
Data Decomposition Based Learning for Load Time-Series Forecasting. 62-74 - Soumajyoti Sarkar, Hamidreza Alvari:
Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org. 75-91 - Fabio Massimo Zennaro:
A Left Realist Critique of the Political Value of Adopting Machine Learning Systems in Criminal Justice. 92-107
Workshop on Parallel, Distributed and Federated Learning (PDFL 2020)
- Cedric Sanders, Thomas Liebig:
Knowledge Discovery on Blockchains: Challenges and Opportunities for Distributed Event Detection Under Constraints. 113-128 - Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik:
Resource-Constrained On-Device Learning by Dynamic Averaging. 129-144
Second Workshop on Machine Learning for Cybersecurity (MLCS 2020)
- Abdelkader Lahmadi, Alexis Duque, Nathan Heraief, Julien Francq:
MitM Attack Detection in BLE Networks Using Reconstruction and Classification Machine Learning Techniques. 149-164 - Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne:
Advocating for Multiple Defense Strategies Against Adversarial Examples. 165-177 - Mark Patrick Roeling, Azqa Nadeem, Sicco Verwer:
Hybrid Connection and Host Clustering for Community Detection in Spatial-Temporal Network Data. 178-204 - Narendra Singh, Harsh Kasyap, Somanath Tripathy:
Collaborative Learning Based Effective Malware Detection System. 205-219
Ninth International Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2020)
- Irem Islek, Sule Gündüz Ögüdücü:
A Hybrid Recommendation System Based on Bidirectional Encoder Representations. 225-236 - Michelangelo Ceci, Angelo Impedovo, Antonio Pellicani:
Leveraging Multi-target Regression for Predicting the Next Parallel Activities in Event Logs. 237-248 - Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri:
A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances. 249-262 - Francesco Folino, Massimo Guarascio, Angelica Liguori, Giuseppe Manco, Luigi Pontieri, Ettore Ritacco:
Exploiting Temporal Convolution for Activity Prediction in Process Analytics. 263-275
Workshop on Data Integration and Applications (DINA 2020)
- Joyce Yu, Jakub Nabaglo, Dinusha Vatsalan, Wilko Henecka, Brian Thorne:
Hyper-Parameter Optimization for Privacy-Preserving Record Linkage. 281-296 - Ben Busath, Jalen Morgan, Joseph Price:
Group-Specific Training Data. 297-302 - Andrew Borthwick, Stephen Ash, Bin Pang, Shehzad Qureshi, Timothy Jones:
Scalable Blocking for Very Large Databases. 303-319 - Yassine Guermazi, Sana Sellami, Omar Boucelma:
Address Validation in Transportation and Logistics: A Machine Learning Based Entity Matching Approach. 320-334 - Hugo Deléglise, Agnès Bégué, Roberto Interdonato, Elodie Maître d'Hôtel, Mathieu Roche, Maguelonne Teisseire:
Linking Heterogeneous Data for Food Security Prediction. 335-344
Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020)
- Evgeniya Korneva, Hendrik Blockeel:
Towards Better Evaluation of Multi-target Regression Models. 353-362 - Neetha Jambigi, Tirtha Chanda, Vishnu Unnikrishnan, Myra Spiliopoulou:
Assessing the Difficulty of Labelling an Instance in Crowdworking. 363-373 - Philipp Behnen, René Keßler, Felix Kruse, Jorge Marx Gómez, Jan Schoenmakers, Sergej Zerr:
Experimental Evaluation of Scale, and Patterns of Systematic Inconsistencies in Google Trends Data. 374-384 - Jonas Rieger, Carsten Jentsch, Jörg Rahnenführer:
Assessing the Uncertainty of the Text Generating Process Using Topic Models. 385-396 - Lorenzo Perini, Connor Galvin, Vincent Vercruyssen:
A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods. 397-408
Second International Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2020)
- Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl:
Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges. 417-431 - Paulo J. G. Lisboa, Sandra Ortega-Martorell, Manoj Jayabalan, Iván Olier:
Efficient Estimation of General Additive Neural Networks: A Case Study for CTG Data. 432-446 - Michal Kuzba, Przemyslaw Biecek:
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations. 447-459 - Giulio Masetti, Felicita Di Giandomenico:
Analyzing Forward Robustness of Feedforward Deep Neural Networks with LeakyReLU Activation Function Through Symbolic Propagation. 460-474 - Vaishnavi Bhargava, Miguel Couceiro, Amedeo Napoli:
LimeOut: An Ensemble Approach to Improve Process Fairness. 475-491 - Jan Ramon, Moitree Basu:
Interpretable Privacy with Optimizable Utility. 492-500 - Francesca Naretto, Roberto Pellungrini, Franco Maria Nardini, Fosca Giannotti:
Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks. 501-516 - Iam Palatnik de Sousa, Marley M. B. R. Vellasco, Eduardo Costa da Silva:
Approximate Explanations for Classification of Histopathology Patches. 517-526
Eighth International Workshop on News Recommendation and Analytics (INRA 2020)
- Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos:
Multi-stakeholder News Recommendation Using Hypergraph Learning. 531-535 - Alberto Cammozzo, Emanuele Di Buccio, Federico Neresini:
Monitoring Technoscientific Issues in the News. 536-553 - Sanne Vrijenhoek, Natali Helberger:
Pitch Proposal: Recommenders with a Mission - Assessing Diversity in News Recommendations. 554-561 - Yujie Xing, Itishree Mohallick, Jon Atle Gulla, Özlem Özgöbek, Lemei Zhang:
An Educational News Dataset for Recommender Systems. 562-570 - Martins Samuel Dogo, Deepak P, Anna Jurek-Loughrey:
Exploring Thematic Coherence in Fake News. 571-580 - Timo Spinde, Felix Hamborg, Bela Gipp:
Media Bias in German News Articles: A Combined Approach. 581-590 - Iknoor Singh, Deepak P, Anoop Kadan:
On the Coherence of Fake News Articles. 591-607
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