Zobrazeno 1 - 10
of 430
pro vyhledávání: '"Nguyen Quoc Viet"'
Autor:
Wang, Zongwei, Gao, Min, Yu, Junliang, Gao, Xinyi, Nguyen, Quoc Viet Hung, Sadiq, Shazia, Yin, Hongzhi
The ID-free recommendation paradigm has been proposed to address the limitation that traditional recommender systems struggle to model cold-start users or items with new IDs. Despite its effectiveness, this study uncovers that ID-free recommender sys
Externí odkaz:
http://arxiv.org/abs/2409.11690
Autor:
Van-Hau Nguyen, Tran Thi Tuyet-Hanh, James Mulhall, Hoang Van Minh, Trung Q Duong, Nguyen Van Chien, Nguyen Thi Trang Nhung, Vu Hoang Lan, Hoang Ba Minh, Do Cuong, Nguyen Ngoc Bich, Nguyen Huu Quyen, Tran Nu Quy Linh, Nguyen Thi Tho, Ngu Duy Nghia, Le Van Quoc Anh, Diep T M Phan, Nguyen Quoc Viet Hung, Mai Thai Son
Publikováno v:
PLoS Neglected Tropical Diseases, Vol 16, Iss 6, p e0010509 (2022)
BackgroundDengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate
Externí odkaz:
https://doaj.org/article/da592396b0394e08ae736e8c42450672
Autor:
Trinh Manh Hung, Nguyen Van Hao, Lam Minh Yen, Angela McBride, Vu Quoc Dat, H. Rogier van Doorn, Huynh Thi Loan, Nguyen Thanh Phong, Martin J. Llewelyn, Behzad Nadjm, Sophie Yacoub, C. Louise Thwaites, Sayem Ahmed, Nguyen Van Vinh Chau, Hugo C. Turner, The Vietnam ICU Translational Applications Laboratory (VITAL) Investigators, Dang Phuong Thao, Dang Trung Kien, Doan Bui Xuan Thy, Dong Huu Khanh Trinh, Du Hong Duc, Ronald Geskus, Ho Bich Hai, Ho Quang Chanh, Ho Van Hien, Huynh Trung Trieu, Evelyne Kestelyn, Le Dinh Van Khoa, Le Thanh Phuong, Luu Hoai Bao Tran, Luu Phuoc An, Angela Mcbride, Nguyen Lam Vuong, Nguyen Quang Huy, Nguyen Than Ha Quyen, Nguyen Thanh Ngoc, Nguyen Thi Giang, Nguyen Thi Le Thanh, Nguyen Thi Phuong Dung, Nguyen Thi Phuong Thao, Ninh Thi Thanh Van, Phan Nguyen Quoc Khanh, Phung Khanh Lam, Phung Tran Huy Nhat, Guy Thwaites, Tran Minh Duc, Jennifer Ilo Van Nuil, Vu Ngo Thanh Huyen, Cao Thi Tam, Duong Bich Thuy, Ha Thi Hai Duong, Ho Dang Trung Nghia, Le Buu Chau, Le Mau Toan, Le Ngoc Minh Thu, Le Thi Mai Thao, Luong Thi Hue Tai, Nguyen Hoan Phu, Nguyen Quoc Viet, Nguyen Thanh Nguyen, Nguyen Thi Kim Anh, Nguyen Van Thanh Duoc, Pham Kieu Nguyet Oanh, Phan Thi Hong Van, Phan Tu Qui, Phan Vinh Tho, Truong Thi Phuong Thao, Natasha Ali, David Clifton, Mike English, Shadi Ghiasi, Heloise Greeff, Jannis Hagenah, Ping Lu, Jacob McKnight, Chris Paton, Pantelis Georgiou, Bernard Hernandez Perez, Kerri Hill-Cawthorne, Alison Holmes, Stefan Karolcik, Damien Ming, Nicolas Moser, Liane Canas, Alberto Gomez, Hamideh Kerdegari, Marc Modat, Reza Razavi, Linda Denehy, Luigi Pisani, Marcus Schultz
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
BackgroundCritically ill patients often require complex clinical care by highly trained staff within a specialized intensive care unit (ICU) with advanced equipment. There are currently limited data on the costs of critical care in low-and middle-inc
Externí odkaz:
https://doaj.org/article/f7077071376a4b659d7c43626ab987a1
As a branch of advanced artificial intelligence, dialogue systems are prospering. Multi-turn response selection is a general research problem in dialogue systems. With the assistance of background information and pre-trained language models, the perf
Externí odkaz:
http://arxiv.org/abs/2407.18479
Recommender systems typically represent users and items by learning their embeddings, which are usually set to uniform dimensions and dominate the model parameters. However, real-world recommender systems often operate in streaming recommendation sce
Externí odkaz:
http://arxiv.org/abs/2407.15411
Autor:
Sakong, Darnbi, Vu, Viet Hung, Huynh, Thanh Trung, Nguyen, Phi Le, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Nguyen, Thanh Tam
Recent advancements in recommender systems have focused on integrating knowledge graphs (KGs) to leverage their auxiliary information. The core idea of KG-enhanced recommenders is to incorporate rich semantic information for more accurate recommendat
Externí odkaz:
http://arxiv.org/abs/2407.03665
Since the creation of the Web, recommender systems (RSs) have been an indispensable mechanism in information filtering. State-of-the-art RSs primarily depend on categorical features, which ecoded by embedding vectors, resulting in excessively large e
Externí odkaz:
http://arxiv.org/abs/2406.17335
Sequential recommender systems have made significant progress. Recently, due to increasing concerns about user data privacy, some researchers have implemented federated learning for sequential recommendation, a.k.a., Federated Sequential Recommender
Externí odkaz:
http://arxiv.org/abs/2406.05387
Autor:
Huynh, Thanh Trung, Nguyen, Trong Bang, Nguyen, Phi Le, Nguyen, Thanh Tam, Weidlich, Matthias, Nguyen, Quoc Viet Hung, Aberer, Karl
Federated learning (FL) has recently emerged as a compelling machine learning paradigm, prioritizing the protection of privacy for training data. The increasing demand to address issues such as ``the right to be forgotten'' and combat data poisoning
Externí odkaz:
http://arxiv.org/abs/2405.18040
Autor:
Gao, Xinyi, Chen, Tong, Zhang, Wentao, Yu, Junliang, Ye, Guanhua, Nguyen, Quoc Viet Hung, Yin, Hongzhi
The increasing prevalence of large-scale graphs poses a significant challenge for graph neural network training, attributed to their substantial computational requirements. In response, graph condensation (GC) emerges as a promising data-centric solu
Externí odkaz:
http://arxiv.org/abs/2405.13707