Efficient texture regularity estimation for second order statistical descriptors. - Attila Tiba; Balázs Harangi; András Hajdu (ISPA, 2017)

Using Laplacian spectrum to analyse the comorbidities network of hemorrhagic stroke. - Attila Bérczes; Tamás Bérczes; Imre Varga; Attila Tiba; Judit Zsuga (CogInfoCom, 2019)

Convolutional Neural Network For Predicting The Spread of Cancer. - Oktavian Lantang; Attila Tiba; András Hajdu; György Terdik (CogInfoCom, 2019)

Detecting outlier and poor quality medical images with an ensemble-based deep learning system. - Attila Tiba; Zsombor Bartik; Henrietta Tomán; András Hajdu (ISPA, 2019)

Optimizing Majority Voting Based Systems Under a Resource Constraint for Multiclass Problems. - Attila Tiba; András Hajdu; György Terdik; Henrietta Tomán (CoRR, 2019)

Binary classifiers' outputs for ensemble creation. - Attila Tiba; András Hajdu; Henrietta Tomán; György Terdik (IEEE DataPort, 2019)

A stochastic approach to handle knapsack problems in the creation of ensembles. - András Hajdu; György Terdik; Attila Tiba; Henrietta Tomán (CoRR, 2020)

A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning. - András Hajdu; György Terdik; Attila Tiba; Henrietta Tomán (Mach. Learn., 2022)

Stochastic and deterministic optimization methods and their applications - Attila Tiba (2022)

A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews. - Robert Lakatos; Gergo Bogacsovics; Balázs Harangi; István Lakatos; Attila Tiba; János Tóth; Marianna Szabo; András Hajdu (CoRR, 2023)

A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. - Robert Lakatos; Gergo Bogacsovics; Balázs Harangi; István Lakatos; Attila Tiba; János Tóth; Marianna Szabo; András Hajdu (Big Data Cogn. Comput., 2024)

Finding Efficient Graph Embeddings and Processing them by a CNN-based Tool. - Attila Tiba; András Hajdu; Tamas Giraszi (Neural Process. Lett., 2024)