Contact:
Room: 502
Position:
Associate Professor
Research teams:
Struktury i metody uczenia sieci neuronowych
Leader of: Struktury i metody uczenia sieci neuronowych
Classes:
Wprowadzenie do systemów operacyjnych wyk
Technika cyfrowa lab
PhD DSc Eng ProfPCz
Jarosław Bilski
Office hours: Pn 11-12, Wt 14-15 - po wcześniejszym umówieniu się.
Papers (33)
2023 (4)
Bilski J., Kowalczyk B., A Novel Approach to the GQR Algorithm for Neural Networks Training. (0)
A Novel Approach to the GQR Algorithm for Neural Networks Training
, 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
Bilski J., Kowalczyk B., Smolag J., A New Computational Approach to the Levenberg-Marquardt Learning Algorithm. (0)
A New Computational Approach to the Levenberg-Marquardt Learning Algorithm
, 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
Bilski J., Kowalczyk B., Smolag J., On Speeding up the Levenberg-Marquardt Learning Algorithm. (0)
On Speeding up the Levenberg-Marquardt Learning Algorithm
, 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
Bilski J., Smolag J., Kowalczyk B., Grzanek K., Izonin I., Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks. (23)
Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks
, 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: 232022 (2)
Bilski J., Kowalczyk B., Kisiel-Dorohinicki M., Siwocha A., Zurada J., Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm. (10)
Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm
, Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 181-195, 2022, Cites: 10
Cierniak R., Bilski J., Pluta P., Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot. (0)
Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot
, 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: 02021 (4)
Bilski J., Kowalczyk B., A New Variant of the GQR Algorithm for Feedforward Neural Networks Training. (1)
A New Variant of the GQR Algorithm for Feedforward Neural Networks Training
, 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: 1
Bilski J., Smolag J., Najgebauer P., Modification of Learning Feedforward Neural Networks with the BP Method. (3)
Modification of Learning Feedforward Neural Networks with the BP Method
, 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: 3
Bilski J., Kowalczyk B., Marjanski A., Gandor M., Zurada J., A Novel Fast Feedforward Neural Networks Training Algorithm. (14)
A Novel Fast Feedforward Neural Networks Training Algorithm
, A Novel Fast Feedforward Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 287-306, 2021, Cites: 14
Bilski J., Rutkowski L., Smolag J., Tao D., A novel method for speed training acceleration of recurrent neural networks. (21)
A novel method for speed training acceleration of recurrent neural networks
, A novel method for speed training acceleration of recurrent neural networks, Information Sciences, 553, 553, 266-279, 2021, Cites: 212020 (3)
Bilski J., Smolag J., Fast Conjugate Gradient Algorithm for Feedforward Neural Networks. (5)
Fast Conjugate Gradient Algorithm for Feedforward Neural Networks
, 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: 5
Bilski J., Kowalczyk B., Zurada J.M., A New Algorithm with a Line Search for Feedforward Neural Networks Training. (0)
A New Algorithm with a Line Search for Feedforward Neural Networks Training
, 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
Bilski J., Kowalczyk B., Marchlewska A., Zurada J.M., Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks. (71)
Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks
, Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 299-316, 2020, Cites: 712019 (2)
Bilski J., Kowalczyk B., Cader A., Modifications of the Givens Training Algorithm for Artificial Neural Networks. (1)
Modifications of the Givens Training Algorithm for Artificial Neural Networks
, 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: 1
Cierniak R., Bilski J., Pluta P., Filutowicz Z., Realizations of the statistical reconstruction method based on the continuous-to-continuous data model. (0)
Realizations of the statistical reconstruction method based on the continuous-to-continuous data model
, 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: 02018 (1)
Bilski J., Kowalczyk B., Grzanek K., The parallel modification to the levenberg-marquardt algorithm. (11)
The parallel modification to the levenberg-marquardt algorithm
, 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: 112017 (3)
Bilski J., Wilamowski B.M., Parallel levenberg-marquardt algorithm without error backpropagation. (12)
Parallel levenberg-marquardt algorithm without error backpropagation
, 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: 12
Bilski J., Kowalczyk B., Zurada J.M., Parallel implementation of the givens rotations in the neural network learning algorithm. (5)
Parallel implementation of the givens rotations in the neural network learning algorithm
, 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: 5
Cierniak R., Bilski J., Smolag J., Pluta P., Shah N., Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography. (1)
Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography
, 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: 12016 (3)
Bilski J., Kowalczyk B., Zurada J.M., Application of the givens rotations in the neural network learning algorithm. (14)
Application of the givens rotations in the neural network learning algorithm
, 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: 14
Bilski J., Galushkin A.I., A new proposition of the activation function for significant improvement of neural networks performance. (3)
A new proposition of the activation function for significant improvement of neural networks performance
, 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
Bilski J., Wilamowski B.M., Parallel learning of feedforward neural networks without error backpropagation. (13)
Parallel learning of feedforward neural networks without error backpropagation
, 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: 132015 (2)
Bilski J., Smolag J., Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks. (39)
Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks
, 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
Bilski J., Smolag J., Zurada J.M., Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks. (23)
Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks
, 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: 232014 (1)
Bilski J., Smolag J., Galushkin A.I., The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks. (27)
The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks
, 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: 272013 (1)
Bilski J., Smolag J., Parallel approach to learning of the recurrent Jordan neural network. (27)
Parallel approach to learning of the recurrent Jordan neural network
, 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: 272012 (1)
Bilski J., Smolag J., Parallel realisation of the recurrent multi layer perceptron learning. (25)
Parallel realisation of the recurrent multi layer perceptron learning
, 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: 252010 (1)
Bilski J., Smolag J., Parallel realisation of the recurrent Elman neural network learning. (25)
Parallel realisation of the recurrent Elman neural network learning
, 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: 252008 (1)
Bilski J., Smolag J., Parallel realisation of the recurrent RTRN neural network learning. (28)
Parallel realisation of the recurrent RTRN neural network learning
, 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: 282004 (3)
Bilski J., Litwinski S., Smolag J., Parallel realisation of QR algorithm for neural networks learning. (21)
Parallel realisation of QR algorithm for neural networks learning
, 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: 21
Bilski J., Smolag J., Zurada J., Systolic architectures for soft computing algorithms. (0)
Systolic architectures for soft computing algorithms
, 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
Bilski J., Momentum modification of the RLS algorithms. (11)
Momentum modification of the RLS algorithms
, Momentum modification of the RLS algorithms, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 151-157, 2004, Cites: 111998 (1)
Bilski J., Rutkowski L., A fast training algorithm for neural networks. (64)
