Igor T. Podolak

According to our database, Igor T. Podolak authored at least 35 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Relative molecule self-attention transformer.

Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski

J. Cheminformatics, December, 2024

2023

Zero time waste in pre-trained early exit neural networks.

Bartosz Wójcik, Marcin Przewiezlikowski, Filip Szatkowski, Maciej Wolczyk, Klaudia Balazy, Bartlomiej Krzepkowski, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski

Neural Networks, November, 2023

Docking-based generative approaches in the search for new drug candidates.

Tomasz Danel, Jan Leski, Sabina Podlewska, Igor T. Podolak

CoRR, 2023

2022

Generative models with kernel distance in data space.

Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak

Neurocomputing, 2022

Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders.

Szymon Knop, Przemyslaw Spurek, Marcin Mazur, Jacek Tabor, Igor T. Podolak

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

2D SIFt: a matrix of ligand-receptor interactions.

Stefan Mordalski, Agnieszka Wojtuch, Igor T. Podolak, Rafal Kurczab, Andrzej J. Bojarski

J. Cheminformatics, 2021

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks.

Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Cramer-Wold Auto-Encoder.

Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski

J. Mach. Learn. Res., 2020

2019

One-element Batch Training by Moving Window.

Przemyslaw Spurek, Szymon Knop, Jacek Tabor, Igor T. Podolak, Bartosz Wójcik

CoRR, 2019

Interpolation in generative models.

Lukasz Struski, Jacek Tabor, Igor T. Podolak, Aleksandra Nowak

CoRR, 2019

Sliced generative models.

Szymon Knop, Marcin Mazur, Jacek Tabor, Igor T. Podolak, Przemyslaw Spurek

CoRR, 2019

Variational auto-encoders for generating feature-preserving automata.

Igor T. Podolak, Adam Roman, Arkadiusz Czekajski, Damian Lesniak, Bartosz Zielinski

Proceedings of the Eleventh Workshop on Non-Classical Models of Automata and Applications, 2019

Distribution-Interpolation Trade off in Generative Models.

Damian Lesniak, Igor Sieradzki, Igor T. Podolak

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

A machine learning approach to synchronization of automata.

Igor T. Podolak, Adam Roman, Marek Szykula, Bartosz Zielinski

Expert Syst. Appl., 2018

On Latent Distributions Without Finite Mean in Generative Models.

Damian Lesniak, Igor Sieradzki, Igor T. Podolak

CoRR, 2018

Cramer-Wold AutoEncoder.

Jacek Tabor, Szymon Knop, Przemyslaw Spurek, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski

CoRR, 2018

2014

Adaptive Active Learning as a Multi-armed Bandit Problem.

Wojciech M. Czarnecki, Igor T. Podolak

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

2013

Theoretical Foundations and Experimental Results for a Hierarchical Classifier with Overlapping Clusters.

Igor T. Podolak, Adam Roman

Comput. Intell., 2013

Density Invariant Detection of Osteoporosis Using Growing Neural Gas.

Igor T. Podolak, Stanislaw K. Jastrzebski

Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 2013

Machine Learning with Known Input Data Uncertainty Measure.

Wojciech M. Czarnecki, Igor T. Podolak

Proceedings of the Computer Information Systems and Industrial Management, 2013

2012

Application of Hierarchical Classifier to Minimal Synchronizing Word Problem.

Igor T. Podolak, Adam Roman, Dariusz Jedrzejczyk

Proceedings of the Artificial Intelligence and Soft Computing, 2012

2011

Risk function estimation for subproblems in a hierarchical classifier.

Igor T. Podolak, Adam Roman

Pattern Recognit. Lett., 2011

CORES: fusion of supervised and unsupervised training methods for a multi-class classification problem.

Igor T. Podolak, Adam Roman

Pattern Anal. Appl., 2011

Hierarchical Estimator.

Stanislaw Brodowski, Igor T. Podolak

Expert Syst. Appl., 2011

Risk Estimation for Hierarchical Classifier.

Igor T. Podolak, Adam Roman

Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

Classifier Ensembles for Virtual Concept Drift - The DEnBoost Algorithm.

Kamil Bartocha, Igor T. Podolak

Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

2009

A New Notion of Weakness in Classification Theory.

Igor T. Podolak, Adam Roman

Proceedings of the Computer Recognition Systems 3, 2009

A Hierarchical Classifier with Growing Neural Gas Clustering.

Igor T. Podolak, Kamil Bartocha

Proceedings of the Adaptive and Natural Computing Algorithms, 9th International Conference, 2009

2008

Hierarchical classifier with overlapping class groups.

Igor T. Podolak

Expert Syst. Appl., 2008

Algorithm for Intelligent Prediction of Requests in Business Systems.

Piotr Kalita, Igor T. Podolak, Adam Roman, Bartosz Bierkowski

Proceedings of the SOFSEM 2008: Theory and Practice of Computer Science, 2008

2007

Hierarchical Rules for a Hierarchical Classifier.

Igor T. Podolak

Proceedings of the Adaptive and Natural Computing Algorithms, 8th International Conference, 2007

2005

Hierarchical Classifier.

Igor T. Podolak, Slawomir Biel, Marcin Bobrowski

Proceedings of the Parallel Processing and Applied Mathematics, 2005

2002

Facial Component Extraction and Face Recognition with Support Vector Machines.

Dihua Xi, Igor T. Podolak, Seong-Whan Lee

Proceedings of the 5th IEEE International Conference on Automatic Face and Gesture Recognition (FGR 2002), 2002

2000

A Hybrid Neural System for Phonematic Transformation.

Igor T. Podolak, Seong-Whan Lee, Andrzej Bielecki, Elzbieta Majkut

Proceedings of the 15th International Conference on Pattern Recognition, 2000

1998

Functional graph model of a neural network.

Igor T. Podolak

IEEE Trans. Syst. Man Cybern. Part B, 1998