Zobrazeno 1 - 10
of 367
pro vyhledávání: '"Woźniak, Michal"'
Mobile network performance modeling typically assumes either a fixed cell's configuration or only considers a limited number of parameters. This prohibits the exploration of multidimensional, diverse configuration space for, e.g., optimization purpos
Externí odkaz:
http://arxiv.org/abs/2407.06702
Autor:
Wojciechowski, Szymon, Woźniak, Michał
One of the significant problems associated with imbalanced data classification is the lack of reliable metrics. This runs primarily from the fact that for most real-life (as well as commonly used benchmark) problems, we do not have information from t
Externí odkaz:
http://arxiv.org/abs/2404.08709
Continual learning poses a fundamental challenge for modern machine learning systems, requiring models to adapt to new tasks while retaining knowledge from previous ones. Addressing this challenge necessitates the development of efficient algorithms
Externí odkaz:
http://arxiv.org/abs/2404.04002
Forecasting natural gas consumption, considering seasonality and trends, is crucial in planning its supply and consumption and optimizing the cost of obtaining it, mainly by industrial entities. However, in times of threats to its supply, it is also
Externí odkaz:
http://arxiv.org/abs/2309.03720
Autor:
Leś, Michał, Woźniak, Michał
Automatic music transcription (AMT) is one of the most challenging tasks in the music information retrieval domain. It is the process of converting an audio recording of music into a symbolic representation containing information about the notes, cho
Externí odkaz:
http://arxiv.org/abs/2305.00426
Publikováno v:
Computational Science ICCS 2021, vol. 1. (LNCS 12742). Springer, pp. 137-150
The paper discusses an approach to decipher large collections of handwritten index cards of historical dictionaries. Our study provides a working solution that reads the cards, and links their lemmas to a searchable list of dictionary entries, for a
Externí odkaz:
http://arxiv.org/abs/2303.16256
Autor:
Kozal, Jędrzej, Woźniak, Michał
Since data is the fuel that drives machine learning models, and access to labeled data is generally expensive, semi-supervised methods are constantly popular. They enable the acquisition of large datasets without the need for too many expert labels.
Externí odkaz:
http://arxiv.org/abs/2301.04420
Autor:
Basterrech, Sebastián, Woźniak, Michal
Recently, continual learning has received a lot of attention. One of the significant problems is the occurrence of \emph{concept drift}, which consists of changing probabilistic characteristics of the incoming data. In the case of the classification
Externí odkaz:
http://arxiv.org/abs/2210.04865
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
Publikováno v:
In Knowledge-Based Systems 25 November 2024 304
