Zobrazeno 1 - 10
of 200
pro vyhledávání: '"Pham, Tan P"'
Robotic manipulators are widely used in various industries for complex and repetitive tasks. However, they remain vulnerable to unexpected hardware failures. In this study, we address the challenge of enabling a robotic manipulator to complete tasks
Externí odkaz:
http://arxiv.org/abs/2409.14435
Multilingual automatic speech recognition (ASR) in the medical domain serves as a foundational task for various downstream applications such as speech translation, spoken language understanding, and voice-activated assistants. This technology enhance
Externí odkaz:
http://arxiv.org/abs/2409.14074
The difference-of-convex (DC) program is a crucial approach to nonconvex optimization problems due to its structure, which encompasses a wide ranges of practical applications. In this paper, we aim to tackle a generalized class of DC programs, where
Externí odkaz:
http://arxiv.org/abs/2409.01535
Knowledge graphs (KGs) enhance the performance of large language models (LLMs) and search engines by providing structured, interconnected data that improves reasoning and context-awareness. However, KGs only focus on text data, thereby neglecting oth
Externí odkaz:
http://arxiv.org/abs/2408.04174
Autor:
Le-Duc, Khai, Zhang, Ryan, Nguyen, Ngoc Son, Pham, Tan-Hanh, Dao, Anh, Ngo, Ba Hung, Nguyen, Anh Totti, Hy, Truong-Son
Vision-language models have been extensively explored across a wide range of tasks, achieving satisfactory performance; however, their application in medical imaging remains underexplored. In this work, we propose a unified framework - LiteGPT - for
Externí odkaz:
http://arxiv.org/abs/2407.12064
In this paper, we consider a class of structured nonconvex nonsmooth optimization problems whose objective function is the sum of three nonconvex functions, one of which is expressed in a difference-of-convex (DC) form. This problem class covers seve
Externí odkaz:
http://arxiv.org/abs/2405.08485
Autor:
Pham, Tan-Hanh, Nguyen, Kim-Doang
Precision devices play an important role in enhancing production quality and productivity in agricultural systems. Therefore, the optimization of these devices is essential in precision agriculture. Recently, with the advancements of deep learning, t
Externí odkaz:
http://arxiv.org/abs/2402.15909
Publikováno v:
Journal of Optimization Theory and Applications (2024)
In this paper, we develop a splitting algorithm incorporating Bregman distances to solve a broad class of linearly constrained composite optimization problems, whose objective function is the separable sum of possibly nonconvex nonsmooth functions an
Externí odkaz:
http://arxiv.org/abs/2401.02635
Autor:
Nguyen, Duy Minh Ho, Pham, Tan Ngoc, Diep, Nghiem Tuong, Phan, Nghi Quoc, Pham, Quang, Tong, Vinh, Nguyen, Binh T., Le, Ngan Hoang, Ho, Nhat, Xie, Pengtao, Sonntag, Daniel, Niepert, Mathias
Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of n
Externí odkaz:
http://arxiv.org/abs/2311.11096
Automated medical image segmentation is becoming increasingly crucial to modern clinical practice, driven by the growing demand for precise diagnosis, the push towards personalized treatment plans, and the advancements in machine learning algorithms,
Externí odkaz:
http://arxiv.org/abs/2310.09998