Zobrazeno 1 - 10
of 30 254
pro vyhledávání: '"P. A. Tuan"'
In future wireless systems of beyond 5G and 6G, addressing diverse applications with varying quality requirements is essential. Open Radio Access Network (O-RAN) architectures offer the potential for dynamic resource adaptation based on traffic deman
Externí odkaz:
http://arxiv.org/abs/2410.02954
Autor:
Wang, Chaoyang, Zhuang, Peiye, Ngo, Tuan Duc, Menapace, Willi, Siarohin, Aliaksandr, Vasilkovsky, Michael, Skorokhodov, Ivan, Tulyakov, Sergey, Wonka, Peter, Lee, Hsin-Ying
We propose 4Real-Video, a novel framework for generating 4D videos, organized as a grid of video frames with both time and viewpoint axes. In this grid, each row contains frames sharing the same timestep, while each column contains frames from the sa
Externí odkaz:
http://arxiv.org/abs/2412.04462
Autor:
Pham, Huy Tuan
Expectation thresholds arise from a class of integer linear programs (LPs) that are fundamental to the study of thresholds in large random systems. An avenue towards estimating expectation thresholds comes from the fractional relaxation of these inte
Externí odkaz:
http://arxiv.org/abs/2412.03540
Recently, deep learning has experienced rapid expansion, contributing significantly to the progress of supervised learning methodologies. However, acquiring labeled data in real-world settings can be costly, labor-intensive, and sometimes scarce. Thi
Externí odkaz:
http://arxiv.org/abs/2411.19143
This paper proposes the possibility of integrating Dynamic Knowledge Graph (DKG) with Software-Defined Networking (SDN). This new approach aims to assist the management and control capabilities of the swarm network. The DKG works as a unified network
Externí odkaz:
http://arxiv.org/abs/2411.19068
Autor:
Vu, Duc Anh, Duy, Nguyen Tran Cong, Wu, Xiaobao, Nhat, Hoang Minh, Mingzhe, Du, Thong, Nguyen Thanh, Luu, Anh Tuan
Large Language Models (LLMs) have shown strong in-context learning (ICL) abilities with a few demonstrations. However, one critical challenge is how to select demonstrations to elicit the full potential of LLMs. In this paper, we propose Curriculum D
Externí odkaz:
http://arxiv.org/abs/2411.18126
Autor:
Shuai, Jiangtao, Baerveldt, Martin, Nguyen-Duc, Manh, Le-Tuan, Anh, Hauswirth, Manfred, Le-Phuoc, Danh
This paper presents a preliminary study of an efficient object tracking approach, comparing the performance of two different 3D point cloud sensory sources: LiDAR and stereo cameras, which have significant price differences. In this preliminary work,
Externí odkaz:
http://arxiv.org/abs/2411.18476
Autor:
Lizarraga, Andrew, Jiang, Eric Hanchen, Nowack, Jacob, Li, Yun Qi, Wu, Ying Nian, Boscoe, Bernie, Do, Tuan
In astrophysics, understanding the evolution of galaxies in primarily through imaging data is fundamental to comprehending the formation of the Universe. This paper introduces a novel approach to conditioning Denoising Diffusion Probabilistic Models
Externí odkaz:
http://arxiv.org/abs/2411.18440
Autor:
Soriano, Jonathan, Saikrishnan, Srinath, Seenivasan, Vikram, Boscoe, Bernie, Singal, Jack, Do, Tuan
In this work, we explore methods to improve galaxy redshift predictions by combining different ground truths. Traditional machine learning models rely on training sets with known spectroscopic redshifts, which are precise but only represent a limited
Externí odkaz:
http://arxiv.org/abs/2411.18054
In recent years, deepfakes (DFs) have been utilized for malicious purposes, such as individual impersonation, misinformation spreading, and artists' style imitation, raising questions about ethical and security concerns. However, existing surveys hav
Externí odkaz:
http://arxiv.org/abs/2411.17911