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ORCID22nd IDA 2024: Stockholm, Sweden - Part II
- Ioanna Miliou
, Nico Piatkowski, Panagiotis Papapetrou:
Advances in Intelligent Data Analysis XXII - 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24-26, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14642, Springer 2024, ISBN 978-3-031-58555-5
Temporal and Sequence Data
- Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. 3-14 - Thabang Lebese, Cécile Mattrand, David Clair, Jean-Marc Bourinet, François Deheeger:
Unsupervised Representation Learning for Smart Transportation. 15-27 - Maedeh Nasri, Thomas Maliappis, Carolien Rieffe, Mitra Baratchi:
T-DANTE: Detecting Group Behaviour in Spatio-Temporal Trajectories Using Context Information. 28-39
Statistical Learning
- Ekaterina Antonenko, Michael Mechenich, Rita Beigaite, Indre Zliobaite, Jesse Read:
Backward Inference in Probabilistic Regressor Chains with Distributional Constraints. 43-55 - Jinyang Yu, Sami Hamdan, Leonard Sasse, Abigail Morrison, Kaustubh R. Patil:
Empirical Comparison Between Cross-Validation and Mutation-Validation in Model Selection. 56-67 - Maciej Krzysztof Zuziak, Salvatore Rinzivillo:
Amplified Contribution Analysis for Federated Learning. 68-79
Data Mining
- Christoph Düsing, Philipp Cimiano:
Monitoring Concept Drift in Continuous Federated Learning Platforms. 83-94 - Pedro C. Vieira, João P. Montrezol, João T. Vieira, João Gama:
S+t-SNE - Bringing Dimensionality Reduction to Data Streams. 95-106 - Joel Dierkes, Daniel Stelter, Christian Braune:
λ-DBSCAN: Augmenting DBSCAN with Prior Knowledge. 107-118 - Vishnu Manasa Devagiri, Pierre Dagnely, Veselka Boeva, Elena Tsiporkova:
Putting Sense into Incomplete Heterogeneous Data with Hypergraph Clustering Analysis. 119-130
Optimization
- Harold Silvère Kiossou, Pierre Schaus, Siegfried Nijssen, Gaël Aglin:
Efficient Lookahead Decision Trees. 133-144 - Lionel Kielhöfer, Felix Mohr, Jan N. van Rijn:
Learning Curve Extrapolation Methods Across Extrapolation Settings. 145-157 - Simon Neumeyer, Julian Stier, Michael Granitzer:
Efficient NAS with FaDE on Hierarchical Spaces. 158-170 - Thore Gerlach, Sascha Mücke:
Investigating the Relation Between Problem Hardness and QUBO Properties. 171-182
XAI
- Henrik Boström:
Example-Based Explanations of Random Forest Predictions. 185-196 - Guillermo Fernández, Riccardo Guidotti, Fosca Giannotti, Mattia Setzu, Juan A. Aledo, José A. Gámez, José Miguel Puerta:
FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. 197-209 - Valentin Lemaire, Gaël Aglin, Siegfried Nijssen:
Interpretable Quantile Regression by Optimal Decision Trees. 210-222 - Anton Björklund, Lauri Seppäläinen, Kai Puolamäki:
SLIPMAP: Fast and Robust Manifold Visualisation for Explainable AI. 223-235 - Federico Mazzoni, Riccardo Guidotti, Alessio Malizia:
A Frank System for Co-Evolutionary Hybrid Decision-Making. 236-248
Industrial Challenge
- Maurizio Parton, Andrea Fois, Michelangelo Vegliò, Carlo Metta, Marco Gregnanin:
Predicting the Failure of Component X in the Scania Dataset with Graph Neural Networks. 251-259 - Louis Carpentier, Arne De Temmerman, Mathias Verbeke:
Towards Contextual, Cost-Efficient Predictive Maintenance in Heavy-Duty Trucks. 260-267 - Jie Zhong, Zhenkan Wang:
Implementing Deep Learning Models for Imminent Component X Failures Prediction in Heavy-Duty Scania Trucks. 268-276
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