Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Piotr Iwo Wójcik"'
Autor:
Piotr Iwo Wójcik, Marcin Kurdziel
Publikováno v:
Pattern Analysis and Applications. 22:1221-1231
Training deep neural networks (DNNs) on high-dimensional data with no spatial structure poses a major computational problem. It implies a network architecture with a huge input layer, which greatly increases the number of weights, often making the tr
Publikováno v:
Neurocomputing. 202:84-90
Deep neural networks have recently shown impressive performance in several machine learning tasks. An important approach to training deep networks, useful especially when labeled data is scarce, relies on unsupervised pretraining of hidden layers fol
Publikováno v:
IEEE Internet Computing. 17:50-59
Can the Google App Engine cloud service be used, free of charge, to execute parameter study problems? That question drove this research, which is founded on the App Engine's newly developed Task Queue API. The authors created a simple and extensible
Publikováno v:
Parallel Processing and Applied Mathematics ISBN: 9783319321486
PPAM (1)
PPAM (1)
Deep learning has recently become a subject of vigorous research in academia and is seeing increasing use in industry. It is often considered a major advance in machine learning. However, deep learning is computationally demanding and therefore requi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a93995cdb822a93d1689927bc2ccd11
https://doi.org/10.1007/978-3-319-32149-3_44
https://doi.org/10.1007/978-3-319-32149-3_44
Publikováno v:
Journal of bioinformatics and computational biology. 13(4)
The search for fast and reliable methods allowing for extraction of biomarker genes, e.g. responsible for a plant resistance to a certain pathogen, is one of the most important and highly exploited data mining problem in bioinformatics. Here we descr
Autor:
Tomasz Grabarczyk, H. Siejkowski, Tomasz Szepieniec, J. Kocot, Piotr Iwo Wójcik, Mariusz Sterzel, Michał Trzeciak, Maciej Golik
Publikováno v:
eScience on Distributed Computing Infrastructure ISBN: 9783319108933
PL-Grid
PL-Grid
While modern Federated Computing Infrastructures --- Grids, Clouds and other technologies --- continuously increase their computing power, their use for research still stays lower than desired. The authors' diagnosis of this problem is a technology b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0f5b08150f5fdd17447886065bc4933
https://doi.org/10.1007/978-3-319-10894-0_10
https://doi.org/10.1007/978-3-319-10894-0_10
Autor:
Mariusz Witek, Adam Padée, Andrzej Olszewski, Anna Padée, Miłosz Zdybał, Piotr Iwo Wójcik, Krzysztof Nawrocki
Publikováno v:
eScience on Distributed Computing Infrastructure ISBN: 9783319108933
PL-Grid
PL-Grid
The large amounts of data collected by the High Energy Physics (HEP) experiments require intensive data processing on a large scale in order to extract their final physics results. In an extreme case – the experiments performed on the Large Hadron
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75531287b0d3db89539ae48c5815fb20
https://doi.org/10.1007/978-3-319-10894-0_16
https://doi.org/10.1007/978-3-319-10894-0_16
Publikováno v:
Computer Science. 16:313
Deep neural networks are often trained in two phases: first hidden layers are pretrained in an unsupervised manner and then network is fine-tuned with error backpropagation. Pretraining is often carried out using Deep Belief Networks (DBNs), with ini