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ORCIDPKDD / ECML 2024: Vilnius, Lithuania - Part IV
- Albert Bifet
, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14944, Springer 2024, ISBN 978-3-031-70358-4
Research Track
- Muhammed Öz, Nicholas Kiefer, Charlotte Debus, Jasmin Hörter, Achim Streit, Markus Götz:
Model Fusion via Neuron Transplantation. 3-19 - Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon:
Compressed Federated Reinforcement Learning with a Generative Model. 20-37 - Hendrik Borras, Bernhard Klein, Holger Fröning:
Walking Noise: On Layer-Specific Robustness of Neural Architectures Against Noisy Computations and Associated Characteristic Learning Dynamics. 38-55 - Pian Qi, Diletta Chiaro, Fabio Giampaolo, Francesco Piccialli:
KAFÈ: Kernel Aggregation for FEderated. 56-71 - Guoqiang Zhang:
On Suppressing Range of Adaptive Stepsizes of Adam to Improve Generalisation Performance. 72-88 - Mei Yu, Yilin Zuo, Wenbin Zhang, Mankun Zhao, Tianyi Xu, Yue Zhao, Jiujiang Guo, Jian Yu:
Graph Attention Network with Relational Dynamic Factual Fusion for Knowledge Graph Completion. 89-106 - Cheng Chen, Bowen Xing, Ivor W. Tsang:
Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding. 107-125 - Tahani Aladwani, Shameem Puthiya Parambath, Christos Anagnostopoulos, Fani Deligianni:
The Price of Labelling: A Two-Phase Federated Self-learning Approach. 126-142 - Zhaopeng Xu, Qi Qin, Bing Liu, Dongyan Zhao:
Disentangled Representations for Continual Learning: Overcoming Forgetting and Facilitating Knowledge Transfer. 143-159 - Mohammed Fellaji, Frédéric Pennerath, Brieuc Conan-Guez, Miguel Couceiro:
On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss. 160-176 - Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim:
Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification. 177-195 - Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh:
Novel Node Category Detection Under Subpopulation Shift. 196-212 - Arthur Zylinski, Abdulhakim Ali Qahtan:
SynODC: Utilizing the Syntactic Structure for Outlier Detection in Categorical Attributes. 213-229 - Simon Malberg, Edoardo Mosca, Georg Groh:
FELIX: Automatic and Interpretable Feature Engineering Using LLMs. 230-246 - Nicolas Urbani, Sylvain Rousseau, Yves Grandvalet, Leonardo Tanzi:
Harnessing Superclasses for Learning from Hierarchical Databases. 247-265 - Benjamin Girault, Rémi Emonet, Amaury Habrard, Jordan Patracone, Marc Sebban:
Approximation Error of Sobolev Regular Functions with Tanh Neural Networks: Theoretical Impact on PINNs. 266-282 - Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu:
A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint. 283-300 - Jordan Patracone, Lucas Anquetil, Yuan Liu, Gilles Gasso, Stéphane Canu:
Linear Modeling of the Adversarial Noise Space. 301-317 - Matteo Ninniri, Marco Podda, Davide Bacciu:
Classifier-Free Graph Diffusion for Molecular Property Targeting. 318-335 - Paulo Yanez Sarmiento, Simon Witzke, Nadja Klein, Bernhard Y. Renard:
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation. 336-351 - Dmitrii Zhemchuzhnikov, Sergei Grudinin:
ILPO-NET: Network for the Invariant Recognition of Arbitrary Volumetric Patterns in 3D. 352-368 - Matthis Manthe, Carole Lartizien, Stefan Duffner:
Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation. 369-385 - Lars Hillebrand, Prabhupad Pradhan, Christian Bauckhage, Rafet Sifa:
Pointer-Guided Pre-training: Infusing Large Language Models with Paragraph-Level Contextual Awareness. 386-402 - Haigen Hu, Jingshan Hong, Kangkang Song, Jinwei Zhu, Weilun Ren:
Cut-Stitch: A Simple and Effective Data Augmentation Method for Industrial Inspection. 403-420 - Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme:
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting. 421-436 - Frédéric Koriche, Jean-Marie Lagniez, Stefan Mengel, Chi Tran:
Learning Model Agnostic Explanations via Constraint Programming. 437-453
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