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ORCIDPKDD/ECML 2023: Turin, Italy - Workshops
- Rosa Meo
, Fabrizio Silvestri:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers, Part II. Communications in Computer and Information Science 2134, Springer 2025, ISBN 978-3-031-74626-0
RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education
- Steve Geinitz:
PICA: A Data-Driven Synthesis of Peer Instruction and Continuous Assessment. 3-17 - Simone Barandoni, Filippo Chiarello, Vito Giordano, Gualtiero Fantoni:
The ChatGPT and Education Tweets Dataset. 18-32 - Mélina Verger, Chunyang Fan, Sébastien Lallé, François Bouchet, Vanda Luengo:
A Fair Post-processing Method Based on the MADD Metric for Predictive Student Models. 33-47 - Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester:
Distractor Generation for Multiple-Choice Questions with Predictive Prompting and Large Language Models. 48-63 - Diana Domenichini, Vito Giordano, Gualtiero Fantoni, Filippo Chiarello:
Towards Personalized Educational Materials: Mapping Student Knowledge Through Natural Language Processing. 64-79 - Francesco Balzan, Andrea Zanellati, Stefano Pio Zingaro, Maurizio Gabbrielli:
A 2-Step Methodology for XAI in Education. 80-86 - Ramona Srbecky, Udo Koeferl, Simon-Alexander Wetzel, Michael Winterhagen, Wieland Fraas, Jan Dettmers, Matthias L. Hemmje:
Consolidation and Transmission of Multiple xAPI Data Sources from Virtual Learning Environments to Different Learning Record Stores. 87-102
SoGood 2023 - 8th Workshop on Data Science for Social Good
- Micha van Grinsven, Matthieu J. S. Brinkhuis, Georg Krempl, Joop Snijder:
Efficient and General Text Classification: An Active Learning Approach Using Active Learning and NLP to Aid Processes Such as Journalistic Investigations And document Analysis. 105-120 - Daniel Emami Riis, Esben Drachmann Rasmussen, Panagiotis Tampakis:
Identifying Features of Constructive Journalism in News Articles: An Explainable ML Approach. 121-136 - Inês Oliveira e Silva, Rita P. Ribeiro, João Gama:
Anomaly Detection in Pet Behavioural Data. 137-153 - Weronika Gutfeter, Joanna Gajewska, Andrzej Pacut:
Detecting Sexually Explicit Content in the Context of the Child Sexual Abuse Materials (CSAM): End-to-End Classifiers and Region-Based Networks. 154-168 - Frederico Lopes, Carlos Soares, Paulo Cortez:
PrivateCTGAN: Adapting GAN for Privacy-Aware Tabular Data Sharing. 169-180 - Marta Barbosa, Carolina Ribeiro, Filipe Gomes, Rita P. Ribeiro, João Gama:
Data Science for Fighting Environmental Crime. 181-196 - Sónia Teixeira, Ana Rita Nogueira, João Gama:
Fairness Analysis in Causal Models: An Application to Public Procurement. 197-211 - Keshav Ramesh, Mahmoud Darwish, Ahmed Sharafath Ahamed Zibli, Nikita Christ Miller, Ali Reza Sajun, Imran A. Zualkernan, Altaf Habib, Andrew Gardner:
Exploring the Generalizability of Transfer Learning for Camera Trap Animal Image Classification. 212-227
Towards Hybrid Human-Machine Learning and Decision Making (HLDM)
- Natalia V. Andrienko, Gennady L. Andrienko, Alexander Artikis, Periklis Mantenoglou, Salvatore Rinzivillo:
Towards a Hybrid Human-Machine Discovery of Complex Movement Patterns. 231-238 - Krishna Sri Ipsit Mantri, Nevasini Sasikumar:
Trustworthy Hybrid Decision-Making. 239-244 - Andrew Fuchs, Andrea Passarella, Marco Conti:
Optimizing Delegation Between Human and AI Collaborative Agents. 245-260 - Deivide Garcia da Silva Oliveira:
Exploring the Risks of General-Purpose AI: The Role of the Brain's Reward Mechanism and Nearsighted Goals in Processes of Decision-Makings. 261-267 - Clara Punzi, Mattia Setzu, Roberto Pellungrini, Fosca Giannotti, Dino Pedreschi:
Towards Synergistic Human-AI Collaboration in Hybrid Decision-Making Systems. 268-275 - Timo Kaufmann, Sarah Ball, Jacob Beck, Eyke Hüllermeier, Frauke Kreuter:
On the Challenges and Practices of Reinforcement Learning from Real Human Feedback. 276-294 - Marco Garofalo, Alessia Fantini, Roberto Pellungrini, Giovanni Pilato, Massimo Villari, Fosca Giannotti:
Conversational XAI: Formalizing Its Basic Design Principles. 295-309 - Ramanakumar Sankar, Kameswara Bharadwaj Mantha, Lucy Fortson, Helen Spiers, Thomas Pengo, Douglas Mashek, Myat Mo, Mark Sanders, Trace Christensen, Jeffrey Salisbury, Laura Trouille:
TCuPGAN: A Novel Framework Developed for Optimizing Human-Machine Interactions in Citizen Science. 310-315 - Ben Wilson, Kayal Lakshmanan, Alan J. Dix, Alma A. M. Rahat, Matt J. Roach:
A Crossroads for Hybrid Human-Machine Decision-Making. 316-322 - Peter Daish, Matt Roach, Alan J. Dix:
Enhancing Fairness, Justice and Accuracy of Hybrid Human-AI Decisions by Shifting Epistemological Stances. 323-331 - John Mark Agosta, Robert Horton, Maryam Tavakoli Hosseinabadi:
Interpreting Dynamic Causal Model Policies. 332-337
Uncertainty Meets Explainability in Machine Learning
- Valerie Krug, Christopher Olson, Sebastian Stober:
Relation of Activity and Confidence When Training Deep Neural Networks. 341-351 - Adrien Le-Coz, Stéphane Herbin, Faouzi Adjed:
Explaining an Image Classifier with a Generative Model Conditioned by Uncertainty. 352-359 - Elena Terzieva, Maximilian Muschalik, Paul Hofman, Eyke Hüllermeier:
Identifying Trends in Feature Attributions During Training of Neural Networks. 360-366 - Kristina Veljkovic, Petar Kochovski, Vlado Stankovski:
Using Stochastic Methods to Setup High Precision Experiments. 367-381 - Didier Dominguez, Dimitris Fotopoulos, Ioanna Chouvarda, Susanna Aussó:
Designing a Method to Identify Explainability Requirements in Cancer Research. 382-388 - Christos N. Mavridis, John S. Baras:
Explainable Learning with Hierarchical Online Deterministic Annealing. 389-403 - Elisabeth R. M. Heremans, Maarten De Vos:
Explaining Uncertainty in AI for Clinical Decision Support Systems. 404-411 - Vasileios Arampatzakis, George Pavlidis, Kyriakos Pantoglou, Nikolaos Mitianoudis, Nikos Papamarkos:
Towards Explainability in Monocular Depth Estimation. 412-419 - Manos Kirtas, Konstantinos Tsampazis, Loukia Avramelou, Nikolaos Passalis, Anastasios Tefas:
Using Part-Based Representations for Explainable Deep Reinforcement Learning. 420-432 - Vasilis Gkolemis, Anargiros Tzerefos, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou:
Regionally Additive Models: Explainable-by-Design Models Minimizing Feature Interactions. 433-447 - Giorgos Giannopoulos, Dimitris Sacharidis, Nikolaos Theologitis, Loukas Kavouras, Ioannis Z. Emiris:
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroups. 448-455
Workshop: Deep Learning and Multimedia Forensics. Combating Fake Media and Misinformation
- Ben Lewis, Victor Sanchez:
Tracing Videos to Their Social Network with Robust DCT Analysis. 459-468 - Daniele Mari, Davide Salvi, Paolo Bestagini, Simone Milani:
All-for-One and One-for-All: Deep Learning-Based Feature Fusion for Synthetic Speech Detection. 469-479 - Vera Cervícková, Martin Pilát:
Improving Tiled Evolutionary Adversarial Attack. 480-490 - Davide Alessandro Coccomini, Roberto Caldelli, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro:
Adversarial Magnification to Deceive Deepfake Detection Through Super Resolution. 491-501 - Alberto Casagrande, Alessio Belli, Cecilia Pasquini, Duc-Tien Dang-Nguyen:
DivNoise: A Data Collection for Source Identification on Diverse Camera Sensors. 502-512 - Roberto Leyva, Gregory Epiphaniou, Carsten Maple, Victor Sanchez:
Detecting Face Synthesis Using a Concealed Fusion Model. 513-524 - Federico Siciliano, Luca Maiano, Lorenzo Papa, Federica Baccini, Irene Amerini, Fabrizio Silvestri:
Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News Without Modifying it. 525-530 - Cecilia Pasquini, Marco Pernpruner, Giada Sciarretta, Silvio Ranise:
Towards a Fine-Grained Threat Model for Video-Based Remote Identity Proofing. 531-536
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