Zobrazeno 1 - 10
of 3 830
pro vyhledávání: '"Van So Le"'
Autor:
Van Hien, Le, Quan, Nguyen Viet
In this paper, we study the generalized differentiability of the metric projection operator onto the positive cone in Hilbert spaces. We first establish the formula for exactly computing the regular coderivative and the Mordukhovich coderivative of t
Externí odkaz:
http://arxiv.org/abs/2407.08007
Autor:
Van Hien, Le
In this paper, we first establish a formula for exactly computing the regular coderivative of the metric projection operator onto closed balls $r\mathbb{B}$ centered at the origin in Hilbert spaces. Then, this result is extended to metric projection
Externí odkaz:
http://arxiv.org/abs/2406.18377
Autor:
Ligaud, Clotilde, Van-Jodin, Lucie Le, Reig, Bruno, Trousset, Pierre, Brunet, Paul, Bertucchi, Michaël, Hellion, Clémence, Gauthier, Nicolas, Van-Hoan, Le, Okuno, Hanako, Dosenovic, Djordje, Cadot, Stéphane, Gassilloud, Remy, Jamet, Matthieu
Two-dimensional (2D) materials like transition metal dichalcogenides (TMD) have proved to be serious candidates to replace silicon in several technologies with enhanced performances. In this respect, the two remaining challenges are the wafer scale g
Externí odkaz:
http://arxiv.org/abs/2405.05693
Autor:
Van Hien, Le
In this paper, we first present a simpler proof of a result on the strict Fr\'echet differentiability of the metric projection operator onto closed balls centered at the origin in Hilbert spaces, which given by Li in \cite{Li24}. Then, based on this
Externí odkaz:
http://arxiv.org/abs/2403.14512
Reinforcement Learning (RL) can effectively learn complex policies. However, learning these policies often demands extensive trial-and-error interactions with the environment. In many real-world scenarios, this approach is not practical due to the hi
Externí odkaz:
http://arxiv.org/abs/2402.10765
Autor:
Nguyen, Dang, Huynh, Phat K., Bui, Vinh Duc An, Hwang, Kee Young, Jain, Nityanand, Nguyen, Chau, Minh, Le Huu Nhat, Van Truong, Le, Nguyen, Xuan Thanh, Nguyen, Dinh Hoang, Dung, Le Tien, Le, Trung Q., Phan, Manh-Huong
The COVID-19 pandemic underscored the importance of reliable, noninvasive diagnostic tools for robust public health interventions. In this work, we fused magnetic respiratory sensing technology (MRST) with machine learning (ML) to create a diagnostic
Externí odkaz:
http://arxiv.org/abs/2311.00737
Autor:
Zafar, Ahtsham, Parthasarathy, Venkatesh Balavadhani, Van, Chan Le, Shahid, Saad, khan, Aafaq Iqbal, Shahid, Arsalan
Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguistic nuance and factual accuracy has proven elusive. In this paper, we first introduce LLMXplorer, a com
Externí odkaz:
http://arxiv.org/abs/2308.13534
Autor:
Chi-Hien Dang, Le-Kim-Thuy Nguyen, Minh-Trong Tran, Van-Dung Le, Nguyen Minh Ty, T. Ngoc Han Pham, Hieu Vu-Quang, Tran Thi Kim Chi, Tran Thi Huong Giang, Nguyen Thi Thanh Tu, Thanh-Danh Nguyen
Publikováno v:
Beilstein Journal of Nanotechnology, Vol 15, Iss 1, Pp 1227-1237 (2024)
This study introduces a highly efficient and straightforward method for synthesizing gold nanoparticles (AuNPs) within a glucosamine/alginate (GluN/Alg) nanocomposite via an ionotropic gelation mechanism in aqueous environment. The resulting nanocomp
Externí odkaz:
https://doaj.org/article/650a9912b7534b5bbc434cb1b1a34518
Publikováno v:
Geodetski Vestnik, Vol 68, Iss 03, Pp 313-326 (2024)
Vietnam is a country with rich mineral resources, of which coal reserves are about 8.6 billion tons, concentrated mainly in the coal basin of Quang Ninh province. Besides the economic and social benefits, coal mining has negative impacts on the envir
Externí odkaz:
https://doaj.org/article/537e4c6cc1454218a4fea6c4f6500841
Publikováno v:
Molecules, Vol 19, Iss 6, Pp 7714-7756 (2014)
Methods of increasing the performance of radionuclide generators used in nuclear medicine radiotherapy and SPECT/PET imaging were developed and detailed for 99Mo/99mTc and 68Ge/68Ga radionuclide generators as the cases. Optimisation methods of the da
Externí odkaz:
https://doaj.org/article/aab5d5581cb14abbb0ecccbd49d4efe7