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pro vyhledávání: '"Macko, Vladimír"'
Autor:
Boža, Vladimír, Macko, Vladimír
Neural networks are often challenging to work with due to their large size and complexity. To address this, various methods aim to reduce model size by sparsifying or decomposing weight matrices, such as magnitude pruning and low-rank or block-diagon
Externí odkaz:
http://arxiv.org/abs/2409.18850
Autor:
Weill, Charles, Gonzalvo, Javier, Kuznetsov, Vitaly, Yang, Scott, Yak, Scott, Mazzawi, Hanna, Hotaj, Eugen, Jerfel, Ghassen, Macko, Vladimir, Adlam, Ben, Mohri, Mehryar, Cortes, Corinna
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspired by the AdaNet algorithm (Cortes et al., 2017) which learns the struc
Externí odkaz:
http://arxiv.org/abs/1905.00080
Finding the best neural network architecture requires significant time, resources, and human expertise. These challenges are partially addressed by neural architecture search (NAS) which is able to find the best convolutional layer or cell that is th
Externí odkaz:
http://arxiv.org/abs/1903.06236
Autor:
Macko, Vladimír
The mass of the Λb baryon has been studied in proton-proton collisions using experimental data from the ATLAS detector at the LHC in CERN. The mass is measured by reconstructing momenta of products in the studied decay. Decay channel Λb → J/ψ(µ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3552628810d7a596207e2e50e8210a50
http://www.nusl.cz/ntk/nusl-456916
http://www.nusl.cz/ntk/nusl-456916
Autor:
Macko, Vladimír, Novacký, Anton
Publikováno v:
Biologia Plantarum; July 1966, Vol. 8 Issue: 4
