Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Ksieniewicz, Paweł"'
Tabular data is considered the last unconquered castle of deep learning, yet the task of data stream classification is stated to be an equally important and demanding research area. Due to the temporal constraints, it is assumed that deep learning me
Externí odkaz:
http://arxiv.org/abs/2407.10807
In the classification tasks, from raw data acquisition to the curation of a dataset suitable for use in evaluating machine learning models, a series of steps - often associated with high costs - are necessary. In the case of Natural Language Processi
Externí odkaz:
http://arxiv.org/abs/2406.10255
Practical applications of artificial intelligence increasingly often have to deal with the streaming properties of real data, which, considering the time factor, are subject to phenomena such as periodicity and more or less chaotic degeneration - res
Externí odkaz:
http://arxiv.org/abs/2404.07776
In recent years Deep Neural Network-based systems are not only increasing in popularity but also receive growing user trust. However, due to the closed-world assumption of such systems, they cannot recognize samples from unknown classes and often ind
Externí odkaz:
http://arxiv.org/abs/2402.06331
The article presents the torchosr package - a Python package compatible with PyTorch library - offering tools and methods dedicated to Open Set Recognition in Deep Neural Networks. The package offers two state-of-the-art methods in the field, a set o
Externí odkaz:
http://arxiv.org/abs/2305.09646
The classification problem's complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning -- becoming the basis for determining meta-attributes or multi-criteria optimiza
Externí odkaz:
http://arxiv.org/abs/2207.06709
The abundance of information in digital media, which in today's world is the main source of knowledge about current events for the masses, makes it possible to spread disinformation on a larger scale than ever before. Consequently, there is a need to
Externí odkaz:
http://arxiv.org/abs/2206.11867
One of the significant problems of streaming data classification is the occurrence of concept drift, consisting of the change of probabilistic characteristics of the classification task. This phenomenon destabilizes the performance of the classificat
Externí odkaz:
http://arxiv.org/abs/2112.10150
Autor:
Kozik, Rafał, Kątek, Gracjan, Gackowska, Marta, Kula, Sebastian, Komorniczak, Joanna, Ksieniewicz, Paweł, Pawlicka, Aleksandra, Pawlicki, Marek, Choraś, Michał
Publikováno v:
In Neurocomputing 1 December 2024 608
Publikováno v:
In Neurocomputing 28 April 2024 579