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Attila Tiba
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2020 – today
- 2024
- [j3]Robert Lakatos
, Gergo Bogacsovics, Balázs Harangi
A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. Big Data Cogn. Comput. 8(3): 20 (2024) - [j2]Attila Tiba, András Hajdu, Tamas Giraszi:
Finding Efficient Graph Embeddings and Processing them by a CNN-based Tool. Neural Process. Lett. 56(5): 226 (2024) - 2023
- [i3]Robert Lakatos, Gergo Bogacsovics, Balázs Harangi, István Lakatos, Attila Tiba, János Tóth, Marianna Szabo, András Hajdu:
A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews. CoRR abs/2306.07786 (2023) - 2022
- [b1]Attila Tiba:
Stochastic and deterministic optimization methods and their applications. University of Debrecen, Hungary, 2022 - [j1]András Hajdu, György Terdik, Attila Tiba
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning. Mach. Learn. 111(4): 1551-1595 (2022) - 2020
- [i2]András Hajdu, György Terdik, Attila Tiba, Henrietta Tomán:
A stochastic approach to handle knapsack problems in the creation of ensembles. CoRR abs/2004.08101 (2020)
2010 – 2019
- 2019
- [c4]Attila Bérczes, Tamás Bérczes, Imre Varga, Attila Tiba
Using Laplacian spectrum to analyse the comorbidities network of hemorrhagic stroke. CogInfoCom 2019: 53-60 - [c3]Oktavian Lantang
Convolutional Neural Network For Predicting The Spread of Cancer. CogInfoCom 2019: 175-180 - [c2]Attila Tiba
Detecting outlier and poor quality medical images with an ensemble-based deep learning system. ISPA 2019: 99-104 - [d1]Attila Tiba, András Hajdu, Henrietta Tomán, György Terdik:
Binary classifiers' outputs for ensemble creation. IEEE DataPort, 2019 - [i1]Attila Tiba, András Hajdu, György Terdik, Henrietta Tomán:
Optimizing Majority Voting Based Systems Under a Resource Constraint for Multiclass Problems. CoRR abs/1904.04360 (2019) - 2017
- [c1]Attila Tiba
Efficient texture regularity estimation for second order statistical descriptors. ISPA 2017: 90-94
Coauthor Index
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last updated on 2024-12-10 20:49 CET by the dblp team
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