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Contact:
Room: 502

Position:
Associate Professor

Research teams:
Struktury i metody uczenia sieci neuronowych
Leader of: Struktury i metody uczenia sieci neuronowych

Classes:
Programowanie wektorowe i równoległe wyk
Programowanie niskopoziomowe wyk
Programowanie niskopoziomowe lab
Systemy operacyjne wyk
PhD DSc Eng Jarosław Bilski

Papers (33)

2023 (4)

On Speeding up the Levenberg-Marquardt Learning Algorithm
Bilski J., Kowalczyk B., Smolag J., On Speeding up the Levenberg-Marquardt Learning Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 12-22, 2023, Cites: 0
Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks
Bilski J., Smolag J., Kowalczyk B., Grzanek K., Izonin I., Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 45-61, 2023, Cites: 12
A Novel Approach to the GQR Algorithm for Neural Networks Training
Bilski J., Kowalczyk B., A Novel Approach to the GQR Algorithm for Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 3-11, 2023, Cites: 0
A New Computational Approach to the Levenberg-Marquardt Learning Algorithm
Bilski J., Kowalczyk B., Smolag J., A New Computational Approach to the Levenberg-Marquardt Learning Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13588 LNAI, 13588 LNAI, 16-26, 2023, Cites: 0

2022 (2)

Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm
Bilski J., Kowalczyk B., Kisiel-Dorohinicki M., Siwocha A., Zurada J., Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 181-195, 2022, Cites: 9
Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot
Cierniak R., Bilski J., Pluta P., Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot, Proceedings of SPIE - The International Society for Optical Engineering, 12304, 12304, 2022, Cites: 0

2021 (4)

A New Variant of the GQR Algorithm for Feedforward Neural Networks Training
Bilski J., Kowalczyk B., A New Variant of the GQR Algorithm for Feedforward Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 41-53, 2021, Cites: 0
Modification of Learning Feedforward Neural Networks with the BP Method
Bilski J., Smolag J., Najgebauer P., Modification of Learning Feedforward Neural Networks with the BP Method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 54-65, 2021, Cites: 2
A novel method for speed training acceleration of recurrent neural networks
Bilski J., Rutkowski L., Smolag J., Tao D., A novel method for speed training acceleration of recurrent neural networks, Information Sciences, 553, 553, 266-279, 2021, Cites: 19
A Novel Fast Feedforward Neural Networks Training Algorithm
Bilski J., Kowalczyk B., Marjanski A., Gandor M., Zurada J., A Novel Fast Feedforward Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 287-306, 2021, Cites: 14

2020 (3)

Fast Conjugate Gradient Algorithm for Feedforward Neural Networks
Bilski J., Smolag J., Fast Conjugate Gradient Algorithm for Feedforward Neural Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 27-38, 2020, Cites: 4
Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks
Bilski J., Kowalczyk B., Marchlewska A., Zurada J.M., Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 299-316, 2020, Cites: 64
A New Algorithm with a Line Search for Feedforward Neural Networks Training
Bilski J., Kowalczyk B., Zurada J.M., A New Algorithm with a Line Search for Feedforward Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 15-26, 2020, Cites: 0

2019 (2)

Modifications of the Givens Training Algorithm for Artificial Neural Networks
Bilski J., Kowalczyk B., Cader A., Modifications of the Givens Training Algorithm for Artificial Neural Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 14-28, 2019, Cites: 0
Realizations of the statistical reconstruction method based on the continuous-to-continuous data model
Cierniak R., Bilski J., Pluta P., Filutowicz Z., Realizations of the statistical reconstruction method based on the continuous-to-continuous data model, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 149-156, 2019, Cites: 0

2018 (1)

The parallel modification to the levenberg-marquardt algorithm
Bilski J., Kowalczyk B., Grzanek K., The parallel modification to the levenberg-marquardt algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 15-24, 2018, Cites: 10

2017 (3)

Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography
Cierniak R., Bilski J., Smolag J., Pluta P., Shah N., Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 473-484, 2017, Cites: 1
Parallel implementation of the givens rotations in the neural network learning algorithm
Bilski J., Kowalczyk B., Zurada J.M., Parallel implementation of the givens rotations in the neural network learning algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 14-24, 2017, Cites: 4
Parallel levenberg-marquardt algorithm without error backpropagation
Bilski J., Wilamowski B.M., Parallel levenberg-marquardt algorithm without error backpropagation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 25-39, 2017, Cites: 11

2016 (3)

Application of the givens rotations in the neural network learning algorithm
Bilski J., Kowalczyk B., Zurada J.M., Application of the givens rotations in the neural network learning algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 46-56, 2016, Cites: 13
A new proposition of the activation function for significant improvement of neural networks performance
Bilski J., Galushkin A.I., A new proposition of the activation function for significant improvement of neural networks performance, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 35-45, 2016, Cites: 3
Parallel learning of feedforward neural networks without error backpropagation
Bilski J., Wilamowski B.M., Parallel learning of feedforward neural networks without error backpropagation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 57-69, 2016, Cites: 12

2015 (2)

Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks
Bilski J., Smolag J., Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks, IEEE Transactions on Parallel and Distributed Systems, 26, 26, 2561-2570, 2015, Cites: 39
Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks
Bilski J., Smolag J., Zurada J.M., Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 3-14, 2015, Cites: 22

2014 (1)

The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks
Bilski J., Smolag J., Galushkin A.I., The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 12-21, 2014, Cites: 26

2013 (1)

Parallel approach to learning of the recurrent Jordan neural network
Bilski J., Smolag J., Parallel approach to learning of the recurrent Jordan neural network, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 32-40, 2013, Cites: 26

2012 (1)

Parallel realisation of the recurrent multi layer perceptron learning
Bilski J., Smolag J., Parallel realisation of the recurrent multi layer perceptron learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 12-20, 2012, Cites: 24

2010 (1)

Parallel realisation of the recurrent Elman neural network learning
Bilski J., Smolag J., Parallel realisation of the recurrent Elman neural network learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 19-25, 2010, Cites: 24

2008 (1)

Parallel realisation of the recurrent RTRN neural network learning
Bilski J., Smolag J., Parallel realisation of the recurrent RTRN neural network learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 11-16, 2008, Cites: 27

2004 (3)

Parallel realisation of QR algorithm for neural networks learning
Bilski J., Litwinski S., Smolag J., Parallel realisation of QR algorithm for neural networks learning, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 158-165, 2004, Cites: 20
Systolic architectures for soft computing algorithms
Bilski J., Smolag J., Zurada J., Systolic architectures for soft computing algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 601-608, 2004, Cites: 0
Momentum modification of the RLS algorithms
Bilski J., Momentum modification of the RLS algorithms, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 151-157, 2004, Cites: 11

1998 (1)

A fast training algorithm for neural networks
Bilski J., Rutkowski L., A fast training algorithm for neural networks, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 45, 45, 749-753, 1998, Cites: 64

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