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ORCID22nd IDA 2024: Stockholm, Sweden - Part I
- 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 I. Lecture Notes in Computer Science 14641, Springer 2024, ISBN 978-3-031-58546-3
Foundations of AI and ML
- Sébastien Ferré:
Tackling the Abstraction and Reasoning Corpus (ARC) with Object-Centric Models and the MDL Principle. 3-15 - Iko Vloothuis, Wouter Duivesteijn:
RMI-RRG: A Soft Protocol to Postulate Monotonicity Constraints for Tabular Datasets. 16-27 - Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy:
A Structural-Clustering Based Active Learning for Graph Neural Networks. 28-40 - Ronald C. van den Broek, Rik Litjens, Tobias Sagis, Nina Verbeeke, Pratik Gajane:
Multi-armed Bandits with Generalized Temporally-Partitioned Rewards. 41-52 - Antonio Di Cecco, Carlo Metta, Marco Fantozzi, Francesco Morandin, Maurizio Parton:
GloNets: Globally Connected Neural Networks. 53-64 - Axel Karlsson, Tianze Wang, Slawomir Nowaczyk, Sepideh Pashami, Sahar Asadi:
Mind the Data, Measuring the Performance Gap Between Tree Ensembles and Deep Learning on Tabular Data. 65-76 - Fabian Hinder, Valerie Vaquet, Barbara Hammer:
A Remark on Concept Drift for Dependent Data. 77-89
Representation Learning
- Antoine Gourru, Charlotte Laclau, Manvi Choudhary, Christine Largeron:
Variational Perspective on Fair Edge Prediction. 93-104 - Wouter W. L. Nuijten, Vlado Menkovski:
Node Classification in Random Trees. 105-116 - Friederike Baier, Sebastian Mair, Samuel G. Fadel:
Self-supervised Siamese Autoencoders. 117-128 - Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofía Calero:
Equivariant Parameter Sharing for Porous Crystalline Materials. 129-140 - Adem Kikaj, Giuseppe Marra, Luc De Raedt:
Subgraph Mining for Graph Neural Networks. 141-152
Applications
- Matías Molina, Rita P. Ribeiro, Bruno Veloso, João Gama:
Super-Resolution Analysis for Landfill Waste Classification. 155-166 - Ylenia Rotalinti, Puja Myles, Allan Tucker:
Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels. 167-178 - Joana Cristo Santos, Miriam Seoane Santos, Pedro Henriques Abreu:
An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification. 179-190 - Pawel Golik, Maciej Grzenda, Elzbieta Sienkiewicz:
Hybrid Ensemble-Based Travel Mode Prediction. 191-202
Natural Language Processing
- Imed Keraghel, Stanislas Morbieu, Mohamed Nadif:
Beyond Words: A Comparative Analysis of LLM Embeddings for Effective Clustering. 205-216 - Vu Minh Hoang Dang, Rakesh M. Verma:
Data Quality in NLP: Metrics and a Comprehensive Taxonomy. 217-229 - Enzo Terreau, Julien Velcin:
Building Brownian Bridges to Learn Dynamic Author Representations from Texts. 230-241 - Tu My Doan, David Baumgartner, Benjamin Kille, Jon Atle Gulla:
Automatically Detecting Political Viewpoints in Norwegian Text. 242-253 - Boshko Koloski, Nada Lavrac, Bojan Cestnik, Senja Pollak, Blaz Skrlj, Andrej Kastrin:
AHAM: Adapt, Help, Ask, Model Harvesting LLMs for Literature Mining. 254-265
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