83 citations · 220 across the 18 of their papers we have counts for
19 papers
StatMix: Data augmentation method that relies on image statistics in federated learning
Dominik Lewy, Jacek Mańdziuk, Maria Ganzha +1
Availability of large amount of annotated data is one of the pillars of deep learning success. Although numerous big datasets have been made available for research, this is often n…
Using adversarial images to improve outcomes of federated learning for non-IID data
Anastasiya Danilenka, Maria Ganzha, Marcin Paprzycki +1
One of the important problems in federated learning is how to deal with unbalanced data. This contribution introduces a novel technique designed to deal with label skewed non-IID d…
Evolutionary Approach to Security Games with Signaling
Adam Żychowski, Jacek Mańdziuk, Elizabeth Bondi +3
Green Security Games have become a popular way to model scenarios involving the protection of natural resources, such as wildlife. Sensors (e.g. drones equipped with cameras) have…
Improving LSHADE by means of a pre-screening mechanism
Mateusz Zaborski, Jacek Mańdziuk
Evolutionary algorithms have proven to be highly effective in continuous optimization, especially when numerous fitness function evaluations (FFEs) are possible. In certain cases,…
A Review of Emerging Research Directions in Abstract Visual Reasoning
Mikołaj Małkiński, Jacek Mańdziuk
Abstract Visual Reasoning (AVR) problems are commonly used to approximate human intelligence. They test the ability of applying previously gained knowledge, experience and skills i…
Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matrices
Mikołaj Małkiński, Jacek Mańdziuk
Abstract visual reasoning (AVR) domain encompasses problems solving which requires the ability to reason about relations among entities present in a given scene. While humans, gene…
Adversarial defenses via a mixture of generators
Maciej Żelaszczyk, Jacek Mańdziuk
In spite of the enormous success of neural networks, adversarial examples remain a relatively weakly understood feature of deep learning systems. There is a considerable effort in…
Prediction of the Facial Growth Direction is Challenging
Stanisław Kaźmierczak, Zofia Juszka, Vaska Vandevska-Radunovic +3
Facial dysmorphology or malocclusion is frequently associated with abnormal growth of the face. The ability to predict facial growth (FG) direction would allow clinicians to prepar…
Audio-to-Image Cross-Modal Generation
Maciej Żelaszczyk, Jacek Mańdziuk
Cross-modal representation learning allows to integrate information from different modalities into one representation. At the same time, research on generative models tends to focu…
Learning Attacker's Bounded Rationality Model in Security Games
Adam Żychowski, Jacek Mańdziuk
The paper proposes a novel neuroevolutionary method (NESG) for calculating leader's payoff in Stackelberg Security Games. The heart of NESG is strategy evaluation neural network (S…
An overview of mixing augmentation methods and augmentation strategies
Dominik Lewy, Jacek Mańdziuk
Deep Convolutional Neural Networks have made an incredible progress in many Computer Vision tasks. This progress, however, often relies on the availability of large amounts of the…
Prediction of the facial growth direction with Machine Learning methods
Stanisław Kaźmierczak, Zofia Juszka, Piotr Fudalej +1
First attempts of prediction of the facial growth (FG) direction were made over half of a century ago. Despite numerous attempts and elapsed time, a satisfactory method has not bee…
Monte Carlo Tree Search: A Review of Recent Modifications and Applications
Maciej Świechowski, Konrad Godlewski, Bartosz Sawicki +1
Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-playing bots or solving sequential decision problems. The method relies on intelligent tree search that bala…
Multi-Label Contrastive Learning for Abstract Visual Reasoning
Mikołaj Małkiński, Jacek Mańdziuk
For a long time the ability to solve abstract reasoning tasks was considered one of the hallmarks of human intelligence. Recent advances in application of deep learning (DL) method…
Biologically Plausible Learning of Text Representation with Spiking Neural Networks
Marcin Białas, Marcin Michał Mirończuk, Jacek Mańdziuk
This study proposes a novel biologically plausible mechanism for generating low-dimensional spike-based text representation. First, we demonstrate how to transform documents into s…
A Committee of Convolutional Neural Networks for Image Classication in the Concurrent Presence of Feature and Label Noise
Stanisław Kaźmierczak, Jacek Mańdziuk
Image classification has become a ubiquitous task. Models trained on good quality data achieve accuracy which in some application domains is already above human-level performance.…
Generalized Self-Adapting Particle Swarm Optimization algorithm with archive of samples
Michał Okulewicz, Mateusz Zaborski, Jacek Mańdziuk
In this paper we enhance Generalized Self-Adapting Particle Swarm Optimization algorithm (GAPSO), initially introduced at the Parallel Problem Solving from Nature 2018 conference,…
Anchoring Theory in Sequential Stackelberg Games
Jan Karwowski, Jacek Mańdziuk, Adam Żychowski
An underlying assumption of Stackelberg Games (SGs) is perfect rationality of the players. However, in real-life situations (which are often modeled by SGs) the followers (terroris…
A Generic Metaheuristic Approach to Sequential Security Games
Adam Żychowski, Jacek Mańdziuk
The paper introduces a generic approach to solving Sequential Security Games (SGs) which utilizes Evolutionary Algorithms. Formulation of the method (named EASG) is general and lar…