| Comparison of GPU and FPGA implementation of SVM algorithm for fast image segmentation M Pietron, M Wielgosz, D Zurek, E Jamro, K Wiatr Architecture of Computing Systems–ARCS 2013: 26th International Conference …, 2013 | 30 | 2013 |
| Ensemble neuroevolution-based approach for multivariate time series anomaly detection K Faber, M Pietron, D Zurek Entropy 23 (11), 1466, 2021 | 28 | 2021 |
| The comparison of parallel sorting algorithms implemented on different hardware platforms D Żurek, M Pietroń, M Wielgosz, K Wiatr Computer Science 14, 679-691, 2013 | 23 | 2013 |
| Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction M Pietroń, D Żurek, B Śnieżyński Journal of Computational Science 67, 101971, 2023 | 14 | 2023 |
| Toward hybrid platform for evolutionary computations of hard discrete problems D Żurek, K Piętak, M Pietroń, M Kisiel-Dorohinicki Procedia Computer Science 108, 877-886, 2017 | 14 | 2017 |
| FPGA implementation of the selected parts of the fast image segmentation M Wielgosz, E Jamro, D Żurek, K Wiatr Intelligent Tools for Building a Scientific Information Platform, 203-216, 2012 | 14 | 2012 |
| Unifying and understanding overparameterized circuit representations via low-rank tensor decompositions A Mari, G Vessio, A Vergari The 6th Workshop on Tractable Probabilistic Modeling, 2023 | 10 | 2023 |
| From MNIST to ImageNet and back: benchmarking continual curriculum learning K Faber, D Zurek, M Pietron, N Japkowicz, A Vergari, R Corizzo Machine Learning 113 (10), 8137-8164, 2024 | 9 | 2024 |
| Striving for performance of discrete optimisation via memetic agent-based systems in a hybrid CPU/GPU environment K Piętak, D Żurek, M Pietroń, A Dymara, M Kisiel-Dorohinicki Journal of Computational Science 31, 151-162, 2019 | 8 | 2019 |
| Evaluation and implementation of n-gram-based algorithm for fast text comparison M Wielgosz, P Szczepka, P Russek, E Jamro, K Wiatr, M Pietroń, D Żurek Computing and Informatics 36 (4), 887-907, 2017 | 7 | 2017 |
| AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection M Pietroń, D Żurek, K Faber, R Corizzo IEEE Transactions on Neural Networks and Learning Systems, 2024 | 3 | 2024 |
| Ada-QPacknet--adaptive pruning with bit width reduction as an efficient continual learning method without forgetting M Pietroń, D Żurek, K Faber, R Corizzo arXiv preprint arXiv:2308.07939, 2023 | 3 | 2023 |
| Ada-QPacknet–Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning M Pietron, D Zurek, K Faber, R Corizzo ECAI 2023, 1882-1889, 2023 | 3 | 2023 |
| A deep neural network as a TABU support in solving LABS problem D Żurek, M Pietroń, K Piętak, M Kisiel-Dorohinicki International Conference on Computational Science, 237-243, 2022 | 3 | 2022 |
| New variants of SDLS algorithm for LABS problem dedicated to GPGPU architectures D Żurek, K Piętak, M Pietroń, M Kisiel-Dorohinicki International Conference on Computational Science, 206-212, 2021 | 3 | 2021 |
| Implementation of algorithms for fast text search and files comparison E Jamro, M Wielgosz, P Russek, M Pietroń, D Żurek, M Janiszewski, ... Proceedings the High Performance Computer Users Conference KU KDM, 83-84, 2013 | 3 | 2013 |
| Solving Multi-Goal Robotic Tasks with Decision Transformer P Gajewski, D Żurek, M Pietroń, K Faber arXiv preprint arXiv:2410.06347, 2024 | 1 | 2024 |
| Towards efficient deep autoencoders for multivariate time series anomaly detection M Pietroń, D Żurek, K Faber, R Corizzo International Conference on Computational Science, 461-469, 2024 | 1 | 2024 |
| Accelerating Deep Convolutional Neural on GPGPU D Żurek, M Pietroń, K Wiatr Intelligent Computing: Proceedings of the 2021 Computing Conference, Volume …, 2021 | 1 | 2021 |
| Training with Reduced Precision of a Support Vector Machine Model for Text Classification D Żurek, M Pietroń, K Wiatr Advances in Information and Communication: Proceedings of the 2021 Future of …, 2021 | 1 | 2021 |
Maciej WielgoszAGH University of Science and TechnologyZweryfikowany adres z agh.edu.pl