A Comparative Study of Assessment Metrics for Imbalanced Learning
Conference Proceeding
Farou, Z., Aharrat, M., & Horváth, T. (2023)
A Comparative Study of Assessment Metrics for Imbalanced Learning. In New Trends in Database and Information Systems: ADBIS 2023 Short Papers, Doctoral Consortium and Workshops: AIDMA, DOING, K-Gals, MADEISD, PeRS, Barcelona, Spain, September 4–7, 2023, Proceedings (119-129). https://doi.org/10.1007/978-3-031-42941-5_11
There are several machine learning algorithms addressing class imbalance problem, requiring standardized metrics for adequete performance evaluation. This paper reviews severa...
Squared Symmetric Formal Contexts and Their Connections with Correlation Matrices
Conference Proceeding
Antoni, L., Eliaš, P., Horváth, T., Krajči, S., Krídlo, O., & Török, C. (2023)
Squared Symmetric Formal Contexts and Their Connections with Correlation Matrices. In Graph-Based Representation and Reasoning: 28th International Conference on Conceptual Structures, ICCS 2023, Berlin, Germany, September 11–13, 2023, Proceedings (19-27). https://doi.org/10.1007/978-3-031-40960-8_2
Formal Concept Analysis identifies hidden patterns in data that can be presented to the user or the data analyst. We propose a method for analyzing the correlation matrices ba...
Solving Multi-class Imbalance Problems Using Improved Tabular GANs
Conference Proceeding
Farou, Z., Kopeikina, L., & Horváth, T. (2022)
Solving Multi-class Imbalance Problems Using Improved Tabular GANs. In H. Yin, D. Camacho, & P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022: 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings (527-539). https://doi.org/10.1007/978-3-031-21753-1_51
Multi-class imbalance problems are non-standard derivative data science problems. These problems are associated with the skewness in the data underlying distribution, which, i...
Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring
Conference Proceeding
Tashu, T. M., & Horváth, T. (2022)
Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring. In H. Yin, D. Camacho, & P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022: 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings (12-21). https://doi.org/10.1007/978-3-031-21753-1_2
Automatic essay scoring (AES) models based on neural networks (NN) have had a lot of success. However, research has shown that NN-based AES models have robustness issues, such...
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series
Conference Proceeding
Skaf, W., & Horváth, T. (2022)
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. In S. Chiusano, T. Cerquitelli, R. Wrembel, K. Nørvåg, B. Catania, G. Vargas-Solar, & E. Zumpano (Eds.), New Trends in Database and Information Systems: ADBIS 2022 Short Papers, Doctoral Consortium and Workshops: DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5–8, 2022, Proceedings (178-187). https://doi.org/10.1007/978-3-031-15743-1_17
Anomalies in time-series provide insights of critical scenarios across a range of industries, from banking and aerospace to information technology, security, and medicine. How...
Directed Undersampling Using Active Learning for Particle Identification
Conference Proceeding
Farou, Z., Ouaari, S., Domian, B., & Horváth, T. (2022)
Directed Undersampling Using Active Learning for Particle Identification. In P. Kumar Singh, Y. Singh, J. Kumar Chhabra, Z. Illés, & C. Verma (Eds.), Recent Innovations in Computing: Proceedings of ICRIC 2021, Volume 2 (149-162). https://doi.org/10.1007/978-981-16-8892-8_12
Migrating Models: A Decentralized View on Federated Learning
Conference Proceeding
Kiss, P., & Horváth, T. (2021)
Migrating Models: A Decentralized View on Federated Learning. In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I (177-191). https://doi.org/10.1007/978-3-030-93736-2_15
Federated learning (FL) researches attempt to alleviate the increasing difficulty of training machine learning models, when the training data is generated in a massively distr...
Time-Series in Hyper-parameter Initialization of Machine Learning Techniques
Conference Proceeding
Horváth, T., Mantovani, R. G., & de Carvalho, A. C. P. L. F. (2021)
Time-Series in Hyper-parameter Initialization of Machine Learning Techniques. In Intelligent Data Engineering and Automated Learning – IDEAL 2021: 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings (246-258). https://doi.org/10.1007/978-3-030-91608-4_25
Initializing the hyper-parameters (HPs) of machine learning (ML) techniques became an important step in the area of automated ML (AutoML). The main premise in HP initializatio...
Attention-Based Multi-modal Emotion Recognition from Art
Conference Proceeding
Tashu, T. M., & Horváth, T. (2021)
Attention-Based Multi-modal Emotion Recognition from Art. In Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part III (604-612). https://doi.org/10.1007/978-3-030-68796-0_43
Emotions are very important in dealing with human decisions, interactions, and cognitive processes. Art is an imaginative human creation that should be appreciated, thought-pr...
A Novel Evaluation Metric for Synthetic Data Generation
Conference Proceeding
Galloni, A., Lendák, I., & Horváth, T. (2020)
A Novel Evaluation Metric for Synthetic Data Generation. In Intelligent Data Engineering and Automated Learning – IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II (25-34). https://doi.org/10.1007/978-3-030-62365-4_3
Differentially private algorithmic synthetic data generation (SDG) solutions take input datasets Dp consisting of sensitive, private data and generate synthetic data Ds with s...