Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Zhenisbek Assylbekov"'
Autor:
Askhat Myngbay, Yergali Bexeitov, Altynai Adilbayeva, Zhenisbek Assylbekov, Bogdan P. Yevstratenko, Rysgul M. Aitzhanova, Bakhyt Matkarimov, Vyacheslav A. Adarichev, Jeannette Kunz
Publikováno v:
Frontiers in Immunology, Vol 10 (2019)
Background: The purpose of this study was to determine whether plasma levels of the collagen triple helix repeat containing 1 (CTHRC1) protein can serve as a blood-based biomarker for improved diagnosis of rheumatoid arthritis (RA) patients and monit
Externí odkaz:
https://doaj.org/article/064495af0e164ca9a436f3e560e2393e
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e7cb1b5f9d150e6dad2816fed7b9cc3
https://doi.org/10.1007/978-3-031-24337-0_26
https://doi.org/10.1007/978-3-031-24337-0_26
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c349f50b08301c586a506064300bb5c
https://doi.org/10.1007/978-3-031-24337-0_7
https://doi.org/10.1007/978-3-031-24337-0_7
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 14:258-270
This work was supported by the Nazarbayev University faculty-development competitive research grants program, Grant Number 240919FD3921, and by the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan, IRN AP051
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8b153d06575196a0e04d3fbb4257566
https://doi.org/10.1002/sam.11506
https://doi.org/10.1002/sam.11506
Autor:
Vassilina Nikoulina, Maxat Tezekbayev, Nuradil Kozhakhmet, Madina Babazhanova, Matthias Gallé, Zhenisbek Assylbekov
There is an ongoing debate in the NLP community whether modern language models contain linguistic knowledge, recovered through so-called probes. In this paper, we study whether linguistic knowledge is a necessary condition for the good performance of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d1e1ae8b72966cdf13e3e53f3b07acd
http://arxiv.org/abs/2103.01819
http://arxiv.org/abs/2103.01819
Publikováno v:
ESANN 2021 proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3df1198761eda0991b1e1f95d2bcfb79
https://doi.org/10.14428/esann/2021.es2021-105
https://doi.org/10.14428/esann/2021.es2021-105
Autor:
Rustem Takhanov, Zhenisbek Assylbekov
Publikováno v:
IJCAI
This paper takes a step towards the theoretical analysis of the relationship between word embeddings and context embeddings in models such as word2vec. We start from basic probabilistic assumptions on the nature of word vectors, context vectors, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::489f959b1919fd703173475cdf978e54
https://doi.org/10.24963/ijcai.2020/718
https://doi.org/10.24963/ijcai.2020/718
Autor:
Alibi Jangeldin, Zhenisbek Assylbekov
Publikováno v:
AI 2020: Advances in Artificial Intelligence ISBN: 9783030649838
Australasian Conference on Artificial Intelligence
Australasian Conference on Artificial Intelligence
We show that removing sigmoid transformation in the skip-gram with negative sampling (SGNS) objective does not harm the quality of word vectors significantly and at the same time is related to factorizing a squashed shifted PMI matrix which, in turn,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03c2f9981e8f71345e761ab038c7cd0a
https://doi.org/10.1007/978-3-030-64984-5_26
https://doi.org/10.1007/978-3-030-64984-5_26
Publikováno v:
AAAI
We critically review the smooth inverse frequency sentence embedding method of Arora, Liang, and Ma (2017), and show inconsistencies in its setup, derivation and evaluation.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2315fb1535b3402777ab7ee7f9d50c1
https://doi.org/10.1609/aaai.v34i10.7190
https://doi.org/10.1609/aaai.v34i10.7190
Publikováno v:
AAAI
We show that the skip-gram embedding of any word can be decomposed into two subvectors which roughly correspond to semantic and syntactic roles of the word.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37914a8acf9fc115e69c0ae90560c9f5
https://doi.org/10.1609/aaai.v34i10.7241
https://doi.org/10.1609/aaai.v34i10.7241