All Outputs (5)

Hyper-parameter initialization of classification algorithms using dynamic time warping: A perspective on PCA meta-features (2022)
Presentation / Conference Contribution
Horváth, T., Mantovani, R. G., & de Carvalho, A. C. Hyper-parameter initialization of classification algorithms using dynamic time warping: A perspective on PCA meta-features

Meta-learning, a concept from the area of automated machine learning, aims at providing decision support for data scientists by recommending a suitable setting (a machine learning algorithm or its hyper-parameters) to be used for a given dataset. Suc... Read More about Hyper-parameter initialization of classification algorithms using dynamic time warping: A perspective on PCA meta-features.

Solving Multi-class Imbalance Problems Using Improved Tabular GANs (2022)
Presentation / Conference Contribution
Farou, Z., Kopeikina, L., & Horváth, T. (2022, November). Solving Multi-class Imbalance Problems Using Improved Tabular GANs. Presented at 23rd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Manchester

Multi-class imbalance problems are non-standard derivative data science problems. These problems are associated with the skewness in the data underlying distribution, which, in turn, raises numerous issues for conventional machine learning techniques... Read More about Solving Multi-class Imbalance Problems Using Improved Tabular GANs.

Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring (2022)
Presentation / Conference Contribution
Tashu, T. M., & Horváth, T. (2022, November). Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring. Presented at 23rd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Manchester

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 that the output of a model changes easily with small changes in the input.... Read More about Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring.

Denoising Architecture for Unsupervised Anomaly Detection in Time-Series (2022)
Presentation / Conference Contribution
Skaf, W., & Horváth, T. (2022, September). Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. Presented at ADBIS 2022: 26th European Conference on Advances in Databases and Information Systems, Turin, Italy

Anomalies in time-series provide insights of critical scenarios across a range of industries, from banking and aerospace to information technology, security, and medicine. However, identifying anomalies in time-series data is particularly challenging... Read More about Denoising Architecture for Unsupervised Anomaly Detection in Time-Series.

Directed Undersampling Using Active Learning for Particle Identification (2022)
Presentation / Conference Contribution
Farou, Z., Ouaari, S., Domian, B., & Horváth, T. (2021, May). Directed Undersampling Using Active Learning for Particle Identification. Presented at 4th International Conference on Recent Innovations in Computing (ICRIC-2021), Central University of Jam