Zobrazeno 1 - 10
of 2 780
pro vyhledávání: '"A. Tsoy"'
Publikováno v:
BMC Cancer, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Purpose Although a long-term goal of cancer therapy always has been the development of agents that selectively destroy cancer cells, more recent trends have been to seek secondary agents that sensitize cancer cells to existing treatment regi
Externí odkaz:
https://doaj.org/article/fd91f30048e147b794a4220b61450f80
It is well-known that Federated Learning (FL) is vulnerable to manipulated updates from clients. In this work we study the impact of data heterogeneity on clients' incentives to manipulate their updates. We formulate a game in which clients may upsca
Externí odkaz:
http://arxiv.org/abs/2412.00980
Autor:
Hartung, Michael, Maier, Andreas, Delgado-Chaves, Fernando, Burankova, Yuliya, Isaeva, Olga I., Patroni, Fábio Malta de Sá, He, Daniel, Shannon, Casey, Kaufmann, Katharina, Lohmann, Jens, Savchik, Alexey, Hartebrodt, Anne, Chervontseva, Zoe, Firoozbakht, Farzaneh, Probul, Niklas, Zotova, Evgenia, Tsoy, Olga, Blumenthal, David B., Ester, Martin, Laske, Tanja, Baumbach, Jan, Zolotareva, Olga
Most complex diseases, including cancer and non-malignant diseases like asthma, have distinct molecular subtypes that require distinct clinical approaches. However, existing computational patient stratification methods have been benchmarked almost ex
Externí odkaz:
http://arxiv.org/abs/2408.00200
Autor:
Tsoy, Eduard N., Suyunov, Laziz A.
Our analysis suggests strongly that stationary pulses exist in nonlinear media with second-, third-, and fourth-order dispersion. A theory, based on the variational approach, is developed for finding approximate parameters of such solitons. It is obt
Externí odkaz:
http://arxiv.org/abs/2405.17848
Autor:
Tsoy, Nikita, Konstantinov, Nikola
Simplicity bias, the propensity of deep models to over-rely on simple features, has been identified as a potential reason for limited out-of-distribution generalization of neural networks (Shah et al., 2020). Despite the important implications, this
Externí odkaz:
http://arxiv.org/abs/2405.17299
Autor:
Liu, Xiaoning, Wu, Zongwei, Li, Ao, Vasluianu, Florin-Alexandru, Zhang, Yulun, Gu, Shuhang, Zhang, Le, Zhu, Ce, Timofte, Radu, Jin, Zhi, Wu, Hongjun, Wang, Chenxi, Ling, Haitao, Cai, Yuanhao, Bian, Hao, Zheng, Yuxin, Lin, Jing, Yuille, Alan, Shao, Ben, Guo, Jin, Liu, Tianli, Wu, Mohao, Feng, Yixu, Hou, Shuo, Lin, Haotian, Zhu, Yu, Wu, Peng, Dong, Wei, Sun, Jinqiu, Zhang, Yanning, Yan, Qingsen, Zou, Wenbin, Yang, Weipeng, Li, Yunxiang, Wei, Qiaomu, Ye, Tian, Chen, Sixiang, Zhang, Zhao, Zhao, Suiyi, Wang, Bo, Luo, Yan, Zuo, Zhichao, Wang, Mingshen, Wang, Junhu, Wei, Yanyan, Sun, Xiaopeng, Gao, Yu, Huang, Jiancheng, Chen, Hongming, Chen, Xiang, Tang, Hui, Chen, Yuanbin, Zhou, Yuanbo, Dai, Xinwei, Qiu, Xintao, Deng, Wei, Gao, Qinquan, Tong, Tong, Li, Mingjia, Hu, Jin, He, Xinyu, Guo, Xiaojie, Sabarinathan, Uma, K, Sasithradevi, A, Bama, B Sathya, Roomi, S. Mohamed Mansoor, Srivatsav, V., Wang, Jinjuan, Sun, Long, Chen, Qiuying, Shao, Jiahong, Zhang, Yizhi, Conde, Marcos V., Feijoo, Daniel, Benito, Juan C., García, Alvaro, Lee, Jaeho, Kim, Seongwan, A, Sharif S M, Khujaev, Nodirkhuja, Tsoy, Roman, Murtaza, Ali, Khairuddin, Uswah, Faudzi, Ahmad 'Athif Mohd, Malagi, Sampada, Joshi, Amogh, Akalwadi, Nikhil, Desai, Chaitra, Tabib, Ramesh Ashok, Mudenagudi, Uma, Lian, Wenyi, Lian, Wenjing, Kalyanshetti, Jagadeesh, Aralikatti, Vijayalaxmi Ashok, Yashaswini, Palani, Upasi, Nitish, Hegde, Dikshit, Patil, Ujwala, C, Sujata, Yan, Xingzhuo, Hao, Wei, Fu, Minghan, choksy, Pooja, Sarvaiya, Anjali, Upla, Kishor, Raja, Kiran, Yan, Hailong, Zhang, Yunkai, Li, Baiang, Zhang, Jingyi, Zheng, Huan
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective network design or solution capable of generating brighter, clearer, and vi
Externí odkaz:
http://arxiv.org/abs/2404.14248
Cross-silo federated learning (FL) allows data owners to train accurate machine learning models by benefiting from each others private datasets. Unfortunately, the model accuracy benefits of collaboration are often undermined by privacy defenses. The
Externí odkaz:
http://arxiv.org/abs/2403.06672
Autor:
Tsoy, Nikita, Konstantinov, Nikola
Collaborative learning techniques have significantly advanced in recent years, enabling private model training across multiple organizations. Despite this opportunity, firms face a dilemma when considering data sharing with competitors -- while colla
Externí odkaz:
http://arxiv.org/abs/2305.16052
Autor:
Tsoy, Andrey1 (AUTHOR) andrey.tsoy@nu.edu.kz, Umbayev, Bauyrzhan1 (AUTHOR) bauyrzhan.umbayev@nu.edu.kz, Kassenova, Aliya1,2 (AUTHOR) aliya.kassenova@nu.edu.kz, Kaupbayeva, Bibifatima1 (AUTHOR) bibifatima.kaupbayeva@nu.edu.kz, Askarova, Sholpan1 (AUTHOR) shaskarova@nu.edu.kz
Publikováno v:
International Journal of Molecular Sciences. Oct2024, Vol. 25 Issue 20, p10964. 18p.
Autor:
Yerdesh, Yelnar, Amanzholov, Tangnur, Aliuly, Abdurashid, Seitov, Abzal, Toleukhanov, Amankeldy, Murugesan, Mohanraj, Botella, Olivier, Feidt, Michel, Wang, Hua Sheng, Tsoy, Alexandr, Belyayev, Yerzhan
Publikováno v:
Energies, MDPI, 2022, 15
The ground source heat pump heating system is considered as one of the best solutions for the transition towards green heating under the continental climate conditions like Kazakhstan. In this paper, experimental and theoretical investigations were c
Externí odkaz:
http://arxiv.org/abs/2211.07693