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Position:
Associate Professor

Classes:
Podstawy sieci komputerowych lab
Systemy rekomendacyjne wyk
Systemy rekomendacyjne lab
Sztuczna inteligencja wyk
Sztuczna inteligencja lab
PhD DSc Eng Piotr Duda

Papers (55)

2021 (1)

The Streaming Approach to Training Restricted Boltzmann Machines
Piotr Duda and Leszek Rutkowski and Piotr Woldan and Patryk Najgebauer, The Streaming Approach to Training Restricted Boltzmann Machines, Springer, Cham, 308-317, 2021, Cites: 0

2020 (19)

Splitting Criteria with the Bias Term
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Splitting Criteria with the Bias Term, Springer, Cham, 83-89, 2020, Cites: 0
Final Remarks and Challenging Problems
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Final Remarks and Challenging Problems, Springer, Cham, 323-327, 2020, Cites: 0
Probabilistic Neural Networks for the Streaming Data Classification
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Probabilistic Neural Networks for the Streaming Data Classification, Springer, Cham, 245-277, 2020, Cites: 1
Basic concepts of data stream mining
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Basic concepts of data stream mining, Springer, Cham, 13-33, 2020, Cites: 9
Misclassification Error Impurity Measure
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Misclassification Error Impurity Measure, Springer, Cham, 63-82, 2020, Cites: 0
Regression
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Regression, Springer, Cham, 309-322, 2020, Cites: 0
A novel drift detection algorithm based on features’ importance analysis in a data streams environment
Piotr Duda and Krzysztof Przybyszewski and Lipo Wang, A novel drift detection algorithm based on features’ importance analysis in a data streams environment, 2020, Cites: 3
General Non-parametric Learning Procedure for Tracking Concept Drift
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, General Non-parametric Learning Procedure for Tracking Concept Drift, Springer, Cham, 155-172, 2020, Cites: 0
Stream data mining: Algorithms and their probabilistic properties
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Stream data mining: Algorithms and their probabilistic properties, Springer, 2020, Cites: 27
Basic Concepts of Probabilistic Neural Networks
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Basic Concepts of Probabilistic Neural Networks, Springer, Cham, 117-154, 2020, Cites: 0
Visual Hybrid Recommendation Systems Based on the Content-Based Filtering
Piotr Woldan and Piotr Duda and Yoichi Hayashi, Visual Hybrid Recommendation Systems Based on the Content-Based Filtering, Springer, Cham, 455-465, 2020, Cites: 0
The General Procedure of Ensembles Construction in Data Stream Scenarios
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, The General Procedure of Ensembles Construction in Data Stream Scenarios, Springer, Cham, 281-286, 2020, Cites: 0
Splitting Criteria Based on the McDiarmid’s Theorem
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Splitting Criteria Based on the McDiarmid’s Theorem, Springer, Cham, 51-62, 2020, Cites: 0
On a Streaming Approach for Training Denoising Auto-encoders
Piotr Duda and Lipo Wang, On a Streaming Approach for Training Denoising Auto-encoders, Springer, Cham, 315-324, 2020, Cites: 1
Hybrid Splitting Criteria
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Hybrid Splitting Criteria, Springer, Cham, 91-113, 2020, Cites: 1
Introduction and Overview of the Main Results of the Book
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Introduction and Overview of the Main Results of the Book, Springer, Cham, 1-10, 2020, Cites: 0
On training deep neural networks using a streaming approach
Piotr Duda and Maciej Jaworski and Andrzej Cader and Lipo Wang, On training deep neural networks using a streaming approach, 2020, Cites: 13
Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks, Springer, Cham, 173-244, 2020, Cites: 0
Decision trees in data stream mining
Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Decision trees in data stream mining, Springer, Cham, 37-50, 2020, Cites: 3

2019 (3)

On handling missing values in data stream mining algorithms based on the restricted Boltzmann machine
Maciej Jaworski and Piotr Duda and Danuta Rutkowska and Leszek Rutkowski, On handling missing values in data stream mining algorithms based on the restricted Boltzmann machine, Springer, Cham, 347-354, 2019, Cites: 2
Corrigendum to ‘How to adjust an ensemble size in stream data mining?’Information Sciences, vol. 381 (2017), pp. 46-54
Lena Pietruczuk and Leszek Rutkowski and Maciej Jaworski and Piotr Duda, Corrigendum to ‘How to adjust an ensemble size in stream data mining?’Information Sciences, vol. 381 (2017), pp. 46-54, Elsevier, 545, 2019, Cites: 0
Resource-aware data stream mining using the Restricted Boltzmann Machine
Maciej Jaworski and Leszek Rutkowski and Piotr Duda and Andrzej Cader, Resource-aware data stream mining using the Restricted Boltzmann Machine, Springer, Cham, 384-396, 2019, Cites: 10

2018 (6)

Online GRNN-based ensembles for regression on evolving data streams
Piotr Duda and Maciej Jaworski and Leszek Rutkowski, Online GRNN-based ensembles for regression on evolving data streams, Springer, Cham, 221-228, 2018, Cites: 7
Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks
Piotr Duda and Maciej Jaworski and Leszek Rutkowski, Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks, Elsevier, 497-518, 2018, Cites: 26
On the Parzen kernel-based probability density function learning procedures over time-varying streaming data with applications to pattern classification
Piotr Duda and Leszek Rutkowski and Maciej Jaworski and Danuta Rutkowska, On the Parzen kernel-based probability density function learning procedures over time-varying streaming data with applications to pattern classification, IEEE, 1683-1696, 2018, Cites: 30
Concept drift detection in streams of labelled data using the restricted Boltzmann machine
Maciej Jaworski and Piotr Duda and Leszek Rutkowski, Concept drift detection in streams of labelled data using the restricted Boltzmann machine, IEEE, 1-7, 2018, Cites: 10
On ensemble components selection in data streams scenario with gradual concept-drift
Piotr Duda, On ensemble components selection in data streams scenario with gradual concept-drift, Springer, Cham, 311-320, 2018, Cites: 2
Convergent time-varying regression models for data streams: Tracking concept drift by the recursive Parzen-based generalized regression neural networks
Piotr Duda and Maciej Jaworski and Leszek Rutkowski, Convergent time-varying regression models for data streams: Tracking concept drift by the recursive Parzen-based generalized regression neural networks, World Scientific Publishing Company, 1750048, 2018, Cites: 29

2017 (5)

New splitting criteria for decision trees in stationary data streams
Maciej Jaworski and Piotr Duda and Leszek Rutkowski, New splitting criteria for decision trees in stationary data streams, IEEE, 2516-2529, 2017, Cites: 78
On applying the restricted Boltzmann machine to active concept drift detection
Maciej Jaworski and Piotr Duda and Leszek Rutkowski, On applying the restricted Boltzmann machine to active concept drift detection, IEEE, 1-8, 2017, Cites: 18
How to adjust an ensemble size in stream data mining?
Lena Pietruczuk and Leszek Rutkowski and Maciej Jaworski and Piotr Duda, How to adjust an ensemble size in stream data mining?, Elsevier, 46-54, 2017, Cites: 65
Heuristic regression function estimation methods for data streams with concept drift
Maciej Jaworski and Piotr Duda and Leszek Rutkowski and Patryk Najgebauer and Miroslaw Pawlak, Heuristic regression function estimation methods for data streams with concept drift, Springer, Cham, 726-737, 2017, Cites: 11
On ensemble components selection in data streams scenario with reoccurring concept-drift
Piotr Duda and Maciej Jaworski and Leszek Rutkowski, On ensemble components selection in data streams scenario with reoccurring concept-drift, IEEE, 1-7, 2017, Cites: 13

2016 (3)

On the Cesàro-Means-Based Orthogonal Series Approach to Learning Time-Varying Regression Functions
Adam Krzyzak Piotr Duda and Lena Pietruczuk and Maciej Jaworski, On the Cesàro-Means-Based Orthogonal Series Approach to Learning Time-Varying Regression Functions, Springer, Cham, 37-48, 2016, Cites: 2
On the Application of Orthogonal Series Density Estimation for Image Classification Based on Feature Description
Piotr Duda and Maciej Jaworski and Lena Pietruczuk and Marcin Korytkowski and Marcin Gabryel and Rafał Scherer, On the Application of Orthogonal Series Density Estimation for Image Classification Based on Feature Description, Springer, Cham, 529-540, 2016, Cites: 0
A method for automatic adjustment of ensemble size in stream data mining
Lena Pietruczuk and Leszek Rutkowski and Maciej Jaworski and Piotr Duda, A method for automatic adjustment of ensemble size in stream data mining, IEEE, 9-15, 2016, Cites: 24

2015 (1)

On the application of fourier series density estimation for image classification based on feature description
Piotr Duda and Maciej Jaworski and Lena Pietruczuk and Rafa l Scherer and Marcin Korytkowski and Marcin Gabryel, On the application of fourier series density estimation for image classification based on feature description, 2015, Cites: 7

2014 (4)

The CART decision tree for mining data streams
Leszek Rutkowski and Maciej Jaworski and Lena Pietruczuk and Piotr Duda, The CART decision tree for mining data streams, Elsevier, 1-15, 2014, Cites: 250
The Parzen kernel approach to learning in non-stationary environment
Lena Pietruczuk and Leszek Rutkowski and Maciej Jaworski and Piotr Duda, The Parzen kernel approach to learning in non-stationary environment, IEEE, 3319-3323, 2014, Cites: 12
A novel application of hoeffding's inequality to decision trees construction for data streams
Piotr Duda and Maciej Jaworski and Lena Pietruczuk and Leszek Rutkowski, A novel application of hoeffding's inequality to decision trees construction for data streams, IEEE, 3324-3330, 2014, Cites: 16
A new method for data stream mining based on the misclassification error
Leszek Rutkowski and Maciej Jaworski and Lena Pietruczuk and Piotr Duda, A new method for data stream mining based on the misclassification error, IEEE, 1048-1059, 2014, Cites: 109

2013 (2)

Adaptation of decision trees for handling concept drift
Lena Pietruczuk and Piotr Duda and Maciej Jaworski, Adaptation of decision trees for handling concept drift, Springer, Berlin, Heidelberg, 459-473, 2013, Cites: 21
Decision trees for mining data streams based on the gaussian approximation
Leszek Rutkowski and Maciej Jaworski and Lena Pietruczuk and Piotr Duda, Decision trees for mining data streams based on the gaussian approximation, IEEE, 108-119, 2013, Cites: 165

2012 (8)

On resources optimization in fuzzy clustering of data streams
Maciej Jaworski and Lena Pietruczuk and Piotr Duda, On resources optimization in fuzzy clustering of data streams, Springer, Berlin, Heidelberg, 92-99, 2012, Cites: 15
On pre-processing algorithms for data stream
Piotr Duda and Maciej Jaworski and Lena Pietruczuk, On pre-processing algorithms for data stream, Springer, Berlin, Heidelberg, 56-63, 2012, Cites: 18
A new fuzzy classifier for data streams
Lena Pietruczuk and Piotr Duda and Maciej Jaworski, A new fuzzy classifier for data streams, Springer, Berlin, Heidelberg, 318-324, 2012, Cites: 19
On the strong convergence of the orthogonal series-type kernel regression neural networks in a non-stationary environment
Piotr Duda and Yoichi Hayashi and Maciej Jaworski, On the strong convergence of the orthogonal series-type kernel regression neural networks in a non-stationary environment, Springer, Berlin, Heidelberg, 47-54, 2012, Cites: 15
On the strong convergence of the recursive orthogonal series-type kernel probabilistic neural networks handling time-varying noise
Piotr Duda and Marcin Korytkowski, On the strong convergence of the recursive orthogonal series-type kernel probabilistic neural networks handling time-varying noise, Springer, Berlin, Heidelberg, 55-62, 2012, Cites: 1
Decision trees for mining data streams based on the McDiarmid's bound
Leszek Rutkowski and Lena Pietruczuk and Piotr Duda and Maciej Jaworski, Decision trees for mining data streams based on the McDiarmid's bound, IEEE, 1272-1279, 2012, Cites: 203
On fuzzy clustering of data streams with concept drift
Maciej Jaworski and Piotr Duda and Lena Pietruczuk, On fuzzy clustering of data streams with concept drift, Springer, Berlin, Heidelberg, 82-91, 2012, Cites: 21
On the uniform convergence of the orthogonal series-type kernel regression neural networks in a time-varying environment
Meng Joo Er and Piotr Duda, On the uniform convergence of the orthogonal series-type kernel regression neural networks in a time-varying environment, Springer, Berlin, Heidelberg, 39-46, 2012, Cites: 0

2011 (3)

On the Cesaro orthogonal series-type kernel probabilistic neural networks handling non-stationary noise
Piotr Duda and Jacek M Zurada, On the Cesaro orthogonal series-type kernel probabilistic neural networks handling non-stationary noise, Springer, Berlin, Heidelberg, 435-442, 2011, Cites: 2
On the weak convergence of the orthogonal series-type kernel regresion neural networks in a non-stationary environment
Meng Joo Er and Piotr Duda, On the weak convergence of the orthogonal series-type kernel regresion neural networks in a non-stationary environment, Springer, Berlin, Heidelberg, 443-450, 2011, Cites: 14
On the weak convergence of the recursive orthogonal series-type kernel probabilistic neural networks in a time-varying environment
Piotr Duda and Yoichi Hayashi, On the weak convergence of the recursive orthogonal series-type kernel probabilistic neural networks in a time-varying environment, Springer, Berlin, Heidelberg, 427-434, 2011, Cites: 0

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