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ORCID10th LOD 2024, Castiglione della Pescaia, Italy - Part II
- Giuseppe Nicosia
, Varun Ojha, Sven Giesselbach, Panos M. Pardalos, Renato Umeton:
Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22-25, 2024, Revised Selected Papers, Part II. Lecture Notes in Computer Science 15509, Springer 2025, ISBN 978-3-031-82483-8 - Ayah Barhrhouj, Bouchra Ananou, Mustapha Ouladsine:
Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring. 1-13 - Emir Yalçin, Kerem Kasikci, Remziye Günes, Melih Güven, Murat Koras, Baris Akgün, Mehmet Gönen:
Identifying Potential Key Point-of-Sale Customers Using Network Centrality. 14-23 - Nihal Acharya Adde, Hanno Gottschalk, Andreas Ebert:
Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning. 24-38 - Alessandro Guazzo, Enrico Longato, Isotta Trescato, Erica Tavazzi, Adriano Chiò, Umberto Manera, Grazia Zocco, Paola Cavalla, Marco Vercellino, Lara Ahmad, Eleonora Tavazzi, Roberto Bergamaschi, Rema Padman, Barbara Di Camillo:
Predicting Multiple Sclerosis Worsening Using Stratification-Based and Time-Dependent Variables Extracted from Routine Visits Data. 39-54 - Vincenzo Miracula, Francesco Mazzeo Rinaldi, Giovanni Giuffrida:
Predicting University Dropout Rates Using Machine Learning: UniCt Case. 55-66 - Nicolò Bellarmino, Alberto Bosio, Riccardo Cantoro, Annachiara Ruospo, Ernesto Sánchez, Giovanni Squillero:
Investigating on Gradient Regularization for Testing Neural Networks. 67-81 - Birgit Kirsch, Xiang Yu, Nilesh Chakraborty, Niclas Doll, Sven Giesselbach, Stefan Rüping:
SKIE-SRL: Structured Key Information Extraction from Business Documents Using Statistical Relational Learning. 82-97 - Christophe Guyeux, David Laiymani, Christophe Sola:
Leveraging LLM-Powered Systems to Accelerate Mycobacterium Tuberculosis Research Step One: From Documents to the Vectorstore. 98-111 - Lys Sanz Moreta, Ibel Carri, Heli M. Garcia Alvarez, Morten Nielsen:
Vegvisir: Probabilistic Model (VAE) for Viral T-Cell Epitope Prediction. 112-130 - Yuchou Chang, Russell Thompson, Christopher Hixenbaugh:
Tiny Long-Short Term Memory Model for Resource-Constrained Prediction of Battery Cycle Life. 131-144 - Stanislav Selitskiy:
Compact Artificial Neural Network Models for Predicting Protein Residue - RNA Base Binding. 145-159 - Nhat Thanh Tran, Jack Xin, Guofa Zhou:
FWin Transformer for Dengue Prediction Under Climate and Ocean Influence. 160-175 - Hubert Bottesch, Christoph Angermann, Christian Laubichler, Constantin Kiesling, Markus Haltmeier:
ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures. 176-189 - Margarita Zaleshina, Alexander Zaleshin:
Topological Layering of Mouse Brain Activity in Light-Sheet Microscopy Datasets. 190-202 - Sven Löffler, Petra Hofstedt:
A Constraint-Based Savings Algorithm for the Traveling Salesman Problem. 203-217 - Aurélien Pion, Emmanuel Vazquez:
Gaussian Process Interpolation with Conformal Prediction: Methods and Comparative Analysis. 218-228 - Sally Ismail, Margarita Anastassova, Mehdi Boukallel, Christian Bolzmacher, Mehdi Ammi:
Using Embeddings of Pre-trained Models for Cross-Database Dysarthria Detection: Supervised vs. Self-supervised Approach. 229-239 - Nicolay Rusnachenko, Huizhi Liang:
Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes. 240-254 - Vangjush Komini, Sarunas Girdzijauskas:
Integrating Logit Space Embeddings for Reliable Out-of-Distribution Detection. 255-269 - Gabriele Romano, Sanket Rajeev Sabharwal, Giorgio Gnecco, Antonio Camurri:
A Computational Framework for Identifying Salient Moments in Motion Capture Data. 270-281 - Marco Reggiannini, Michela Martinelli, Oscar Papini, Lorenzo Zacchetti, Filippo Domenichetti, Gabriele Pieri:
Machine Learning for the Evaluation of the Nephrops norvegicus Population. 282-295 - Ryan Hodgson, Alexandra I. Cristea, John Graham:
Enhancing Cluster-Based Topic Models Through Parametric Dimensionality Reduction with Transformer-Encoders. 296-311 - Jaune Malukaite, Povilas Treigys, Jolita Bernataviciene:
Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification. 312-322 - Ang Li, Peter J. Stuckey, Sven Koenig, T. K. Satish Kumar:
Rapidly Computing Approximate Graph Convex Hulls via FastMap. 323-338 - Matthias Schwab, Agnes Mayr, Markus Haltmeier:
Deep Gaussian Mixture Model for Unsupervised Image Segmentation. 339-352 - Baris Bayram, Alaeddin Türkmen, Ayse Dilara Türkmen, Merve Karademir:
Address Classification in E-Commerce Logistics Using Federated Learning. 353-360
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