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Prowadzone zajęcia:
Systemy rekomendacyjne lab
Systemy rekomendacyjne wyk
Sztuczna inteligencja lab
Sztuczna inteligencja wyk
Metody przetwarzania języka naturalnego lab
Metody przetwarzania języka naturalnego wyk
dr hab. prof. PCz Piotr Duda

Publikacje (62)

2024 (3)

(μ +λ) Evolution Strategy with Socio-Cognitive Mutation
Urbanczyk A., Kucaba K., Wojtulewicz M., Kisiel-Dorohinicki M., Rutkowski L., Duda P., Kacprzyk J., Yao X., Chong S.Y., Byrski A., (μ +λ) Evolution Strategy with Socio-Cognitive Mutation, Journal of Automation, Mobile Robotics and Intelligent Systems, 18, 18, 1-11, 2024, Liczba cytowań: 0
Accelerating deep neural network learning using data stream methodology
Duda P., Wojtulewicz M., Rutkowski L., Accelerating deep neural network learning using data stream methodology, Information Sciences, 669, 669, 2024, Liczba cytowań: 1
Probabilistic neural networks for incremental learning over time-varying streaming data with application to air pollution monitoring
Rutkowska D., Duda P., Cao J., Jaworski M., Kisiel-Dorohinicki M., Tao D., Rutkowski L., Probabilistic neural networks for incremental learning over time-varying streaming data with application to air pollution monitoring, Applied Soft Computing, 161, 161, 2024, Liczba cytowań: 0

2023 (4)

Dynamic Signature Verification Using Selected Regions
Zalasinski M., Duda P., Lota S., Cpalka K., Dynamic Signature Verification Using Selected Regions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 388-397, 2023, Liczba cytowań: 1
The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach
Duda P., Wojtulewicz M., Rutkowski L., The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 46-55, 2023, Liczba cytowań: 0
The L<inf>2</inf> convergence of stream data mining algorithms based on probabilistic neural networks
Rutkowska D., Duda P., Cao J., Rutkowski L., Byrski A., Jaworski M., Tao D., The L<inf>2</inf> convergence of stream data mining algorithms based on probabilistic neural networks, Information Sciences, 631, 631, 346-368, 2023, Liczba cytowań: 6
A New Approach to Image-Based Recommender Systems with the Application of Heatmaps Maps
Woldan P., Duda P., Cader A., Laktionov I., A New Approach to Image-Based Recommender Systems with the Application of Heatmaps Maps, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 63-72, 2023, Liczba cytowań: 5

2022 (1)

Noise Robust Illumination Invariant Face Recognition Via Bivariate Wavelet Shrinkage in Logarithm Domain
Chen G.Y., Krzyzak A., Duda P., Cader A., Noise Robust Illumination Invariant Face Recognition Via Bivariate Wavelet Shrinkage in Logarithm Domain, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 169-180, 2022, Liczba cytowań: 4

2021 (1)

The Streaming Approach to Training Restricted Boltzmann Machines
Duda P., Rutkowski L., Woldan P., Najgebauer P., The Streaming Approach to Training Restricted Boltzmann Machines, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 308-317, 2021, Liczba cytowań: 0

2020 (20)

Decision Trees in Data Stream Mining
Rutkowski L., Jaworski M., Duda P., Decision Trees in Data Stream Mining, Studies in Big Data, 56, 56, 37-50, 2020, Liczba cytowań: 7
Misclassification Error Impurity Measure
Rutkowski L., Jaworski M., Duda P., Misclassification Error Impurity Measure, Studies in Big Data, 56, 56, 63-82, 2020, Liczba cytowań: 2
The General Procedure of Ensembles Construction in Data Stream Scenarios
Rutkowski L., Jaworski M., Duda P., The General Procedure of Ensembles Construction in Data Stream Scenarios, Studies in Big Data, 56, 56, 281-286, 2020, Liczba cytowań: 0
Splitting Criteria Based on the McDiarmid’s Theorem
Rutkowski L., Jaworski M., Duda P., Splitting Criteria Based on the McDiarmid’s Theorem, Studies in Big Data, 56, 56, 51-62, 2020, Liczba cytowań: 0
Hybrid Splitting Criteria
Rutkowski L., Jaworski M., Duda P., Hybrid Splitting Criteria, Studies in Big Data, 56, 56, 91-113, 2020, Liczba cytowań: 1
On a Streaming Approach for Training Denoising Auto-encoders
Duda P., Wang L., On a Streaming Approach for Training Denoising Auto-encoders, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 315-324, 2020, Liczba cytowań: 0
Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks
Rutkowski L., Jaworski M., Duda P., Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks, Studies in Big Data, 56, 56, 173-244, 2020, Liczba cytowań: 1
Final Remarks and Challenging Problems
Rutkowski L., Jaworski M., Duda P., Final Remarks and Challenging Problems, Studies in Big Data, 56, 56, 323-327, 2020, Liczba cytowań: 0
On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification
Duda P., Rutkowski L., Jaworski M., Rutkowska D., On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification, IEEE Transactions on Cybernetics, 50, 50, 1683-1696, 2020, Liczba cytowań: 32
Probabilistic Neural Networks for the Streaming Data Classification
Rutkowski L., Jaworski M., Duda P., Probabilistic Neural Networks for the Streaming Data Classification, Studies in Big Data, 56, 56, 245-277, 2020, Liczba cytowań: 2
General Non-parametric Learning Procedure for Tracking Concept Drift
Rutkowski L., Jaworski M., Duda P., General Non-parametric Learning Procedure for Tracking Concept Drift, Studies in Big Data, 56, 56, 155-172, 2020, Liczba cytowań: 1
Basic Concepts of Probabilistic Neural Networks
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Probabilistic Neural Networks, Studies in Big Data, 56, 56, 117-154, 2020, Liczba cytowań: 0
On Training Deep Neural Networks Using a Streaming Approach
Duda P., Jaworski M., Cader A., Wang L., On Training Deep Neural Networks Using a Streaming Approach, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 15-26, 2020, Liczba cytowań: 24
Splitting Criteria with the Bias Term
Rutkowski L., Jaworski M., Duda P., Splitting Criteria with the Bias Term, Studies in Big Data, 56, 56, 83-89, 2020, Liczba cytowań: 0
Visual Hybrid Recommendation Systems Based on the Content-Based Filtering
Woldan P., Duda P., Hayashi Y., Visual Hybrid Recommendation Systems Based on the Content-Based Filtering, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 455-465, 2020, Liczba cytowań: 3
Basic Concepts of Data Stream Mining
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Data Stream Mining, Studies in Big Data, 56, 56, 13-33, 2020, Liczba cytowań: 18
Introduction and Overview of the Main Results of the Book
Rutkowski L., Jaworski M., Duda P., Introduction and Overview of the Main Results of the Book, Studies in Big Data, 56, 56, 1-10, 2020, Liczba cytowań: 1
Classification
Rutkowski L., Jaworski M., Duda P., Classification, Studies in Big Data, 56, 56, 287-308, 2020, Liczba cytowań: 0
A Novel Drift Detection Algorithm Based on Features' Importance Analysis in a Data Streams Environment
Duda P., Przybyszewski K., Wang L., A Novel Drift Detection Algorithm Based on Features' Importance Analysis in a Data Streams Environment, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 287-298, 2020, Liczba cytowań: 7
Regression
Rutkowski L., Jaworski M., Duda P., Regression, Studies in Big Data, 56, 56, 309-322, 2020, Liczba cytowań: 0

2019 (3)

Resource-aware data stream mining using the restricted boltzmann machine
Jaworski M., Rutkowski L., Duda P., Cader A., Resource-aware data stream mining using the restricted boltzmann machine, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 384-396, 2019, Liczba cytowań: 4
Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028))
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028)), Information Sciences, 477, 477, 545, 2019, Liczba cytowań: 0
On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine
Jaworski M., Duda P., Rutkowska D., Rutkowski L., On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine, Communications in Computer and Information Science, 1143 CCIS, 1143 CCIS, 347-354, 2019, Liczba cytowań: 2

2018 (6)

Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks
Duda P., Jaworski M., Rutkowski L., Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks, Information Sciences, 460-461, 460-461, 497-518, 2018, Liczba cytowań: 24
Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks
Duda P., Jaworski M., Rutkowski L., Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks, International Journal of Neural Systems, 28, 28, 2018, Liczba cytowań: 31
On ensemble components selection in data streams scenario with gradual concept-drift
Duda P., On ensemble components selection in data streams scenario with gradual concept-drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 311-320, 2018, Liczba cytowań: 3
Online grnn-based ensembles for regression on evolving data streams
Duda P., Jaworski M., Rutkowski L., Online grnn-based ensembles for regression on evolving data streams, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10878 LNCS, 10878 LNCS, 221-228, 2018, Liczba cytowań: 6
Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine
Jaworski M., Duda P., Rutkowski L., Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine, Proceedings of the International Joint Conference on Neural Networks, 2018-July, 2018-July, 2018, Liczba cytowań: 13
New Splitting Criteria for Decision Trees in Stationary Data Streams
Jaworski M., Duda P., Rutkowski L., New Splitting Criteria for Decision Trees in Stationary Data Streams, IEEE Transactions on Neural Networks and Learning Systems, 29, 29, 2516-2529, 2018, Liczba cytowań: 89

2017 (4)

How to adjust an ensemble size in stream data mining?
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., How to adjust an ensemble size in stream data mining?, Information Sciences, 381, 381, 46-54, 2017, Liczba cytowań: 65
On applying the Restricted Boltzmann Machine to active concept drift detection
Jaworski M., Duda P., Rutkowski L., On applying the Restricted Boltzmann Machine to active concept drift detection, 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, 2018-January, 2018-January, 1-8, 2017, Liczba cytowań: 22
Heuristic regression function estimation methods for data streams with concept drift
Jaworski M., Duda P., Rutkowski L., Najgebauer P., Pawlak M., Heuristic regression function estimation methods for data streams with concept drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 726-737, 2017, Liczba cytowań: 10
On ensemble components selection in data streams scenario with reoccurring concept-drift
Duda P., Jaworski M., Rutkowski L., On ensemble components selection in data streams scenario with reoccurring concept-drift, 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, 2018-January, 2018-January, 1-7, 2017, Liczba cytowań: 16

2016 (3)

A method for automatic adjustment of ensemble size in stream data mining
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., A method for automatic adjustment of ensemble size in stream data mining, Proceedings of the International Joint Conference on Neural Networks, 2016-October, 2016-October, 9-15, 2016, Liczba cytowań: 18
On the Cesàro-means-based orthogonal series approach to learning time-varying regression functions
Duda P., Pietruczuk L., Jaworski M., Krzyzak A., On the Cesàro-means-based orthogonal series approach to learning time-varying regression functions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 37-48, 2016, Liczba cytowań: 2
On the application of orthogonal series density estimation for image classification based on feature description
Duda P., Jaworski M., Pietruczuk L., Korytkowski M., Gabryel M., Scherer R., On the application of orthogonal series density estimation for image classification based on feature description, Advances in Intelligent Systems and Computing, 364, 364, 529-540, 2016, Liczba cytowań: 1

2015 (1)

A new method for data stream mining based on the misclassification error
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., A new method for data stream mining based on the misclassification error, IEEE Transactions on Neural Networks and Learning Systems, 26, 26, 1048-1059, 2015, Liczba cytowań: 104

2014 (4)

Decision trees for mining data streams based on the gaussian approximation
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., Decision trees for mining data streams based on the gaussian approximation, IEEE Transactions on Knowledge and Data Engineering, 26, 26, 108-119, 2014, Liczba cytowań: 144
The CART decision tree for mining data streams
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., The CART decision tree for mining data streams, Information Sciences, 266, 266, 1-15, 2014, Liczba cytowań: 270
A novel application of Hoeffding's inequality to decision trees construction for data streams
Duda P., Jaworski M., Pietruczuk L., Rutkowski L., A novel application of Hoeffding's inequality to decision trees construction for data streams, Proceedings of the International Joint Conference on Neural Networks, 3324-3330, 2014, Liczba cytowań: 16
The Parzen kernel approach to learning in non-stationary environment
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., The Parzen kernel approach to learning in non-stationary environment, Proceedings of the International Joint Conference on Neural Networks, 3319-3323, 2014, Liczba cytowań: 12

2013 (2)

Decision trees for mining data streams based on the mcdiarmid's bound
Rutkowski L., Pietruczuk L., Duda P., Jaworski M., Decision trees for mining data streams based on the mcdiarmid's bound, IEEE Transactions on Knowledge and Data Engineering, 25, 25, 1272-1279, 2013, Liczba cytowań: 168
Adaptation of decision trees for handling concept drift
Pietruczuk L., Duda P., Jaworski M., Adaptation of decision trees for handling concept drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 459-473, 2013, Liczba cytowań: 22

2012 (10)

On the weak convergence of the recursive orthogonal series-type kernel probabilistic neural networks in a time-varying environment
Duda P., Hayashi Y., On the weak convergence of the recursive orthogonal series-type kernel probabilistic neural networks in a time-varying environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7203 LNCS, 7203 LNCS, 427-434, 2012, Liczba cytowań: 0
On the strong convergence of the orthogonal series-type kernel regression neural networks in a non-stationary environment
Duda P., Hayashi Y., Jaworski M., On the strong convergence of the orthogonal series-type kernel regression neural networks in a non-stationary environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 47-54, 2012, Liczba cytowań: 17
On the Cesaro orthogonal series-type kernel probabilistic neural networks handling non-stationary noise
Duda P., Zurada J.M., On the Cesaro orthogonal series-type kernel probabilistic neural networks handling non-stationary noise, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7203 LNCS, 7203 LNCS, 435-442, 2012, Liczba cytowań: 1
On the uniform convergence of the orthogonal series-type kernel regression neural networks in a time-varying environment
Er M.J., Duda P., On the uniform convergence of the orthogonal series-type kernel regression neural networks in a time-varying environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 39-46, 2012, Liczba cytowań: 0
On resources optimization in fuzzy clustering of data streams
Jaworski M., Pietruczuk L., Duda P., On resources optimization in fuzzy clustering of data streams, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 92-99, 2012, Liczba cytowań: 17
On fuzzy clustering of data streams with concept drift
Jaworski M., Duda P., Pietruczuk L., On fuzzy clustering of data streams with concept drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 82-91, 2012, Liczba cytowań: 18
On pre-processing algorithms for data stream
Duda P., Jaworski M., Pietruczuk L., On pre-processing algorithms for data stream, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 56-63, 2012, Liczba cytowań: 18
A new fuzzy classifier for data streams
Pietruczuk L., Duda P., Jaworski M., A new fuzzy classifier for data streams, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 318-324, 2012, Liczba cytowań: 18
On the strong convergence of the recursive orthogonal series-type kernel probabilistic neural networks handling time-varying noise
Duda P., Korytkowski M., On the strong convergence of the recursive orthogonal series-type kernel probabilistic neural networks handling time-varying noise, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 55-62, 2012, Liczba cytowań: 0
On the weak convergence of the orthogonal series-type kernel regresion neural networks in a non-stationary environment
Er M.J., Duda P., On the weak convergence of the orthogonal series-type kernel regresion neural networks in a non-stationary environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7203 LNCS, 7203 LNCS, 443-450, 2012, Liczba cytowań: 14

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