Zobrazeno 1 - 10
of 6 111
pro vyhledávání: '"YUAN Shuai"'
Robotic manipulation has made significant advancements, with systems demonstrating high precision and repeatability. However, this remarkable precision often fails to translate into efficient manipulation of thin deformable objects. Current robotic s
Externí odkaz:
http://arxiv.org/abs/2411.13952
Autor:
Yuan, Shuai S. A., Xu, Xinyi Y. I., Yuan, Jinpeng, Xie, Guoda, Huang, Chongwen, Chen, Xiaoming, Huang, Zhixiang, Sha, Wei E. I.
Rydberg atom-based antennas exploit the quantum properties of highly excited Rydberg atoms, providing unique advantages over classical antennas, such as high sensitivity, broad frequency range, and compact size. Despite the increasing interests in th
Externí odkaz:
http://arxiv.org/abs/2411.08570
Although binary classification is a well-studied problem, training reliable classifiers under severe class imbalance remains a challenge. Recent techniques mitigate the ill effects of imbalance on training by modifying the loss functions or optimizat
Externí odkaz:
http://arxiv.org/abs/2410.03588
Autor:
Jiang, Yutong, Ge, Hangyu, Wang, Bi-Ying, Yuan, Shuai S. A., Pan, Shi-Jie, Xu, Hongjing, Cui, Xiaopeng, Yung, Man-Hong, Liu, Feng, Sha, Wei E. I.
This paper introduces an innovative quantum-inspired method for beamforming (BF) optimization in multiple-input multiple-output (MIMO) arrays. The method leverages the simulated bifurcation (SB) algorithm to address the complex combinatorial optimiza
Externí odkaz:
http://arxiv.org/abs/2409.19938
The expansive storage capacity and robust computational power of cloud servers have led to the widespread outsourcing of machine learning inference services to the cloud. While this practice offers significant operational benefits, it also poses subs
Externí odkaz:
http://arxiv.org/abs/2409.19334
Autor:
Yuan, Shuai, Li, Hongwei, Han, Xingshuo, Xu, Guowen, Jiang, Wenbo, Ni, Tao, Zhao, Qingchuan, Fang, Yuguang
Physical adversarial patches have emerged as a key adversarial attack to cause misclassification of traffic sign recognition (TSR) systems in the real world. However, existing adversarial patches have poor stealthiness and attack all vehicles indiscr
Externí odkaz:
http://arxiv.org/abs/2409.12394
In this paper the neutral 2SC phase of color superconductivity is investigated in the presence of a magnetic field and for diquark coupling constants and baryonic densities that are expected to characterize neutron stars. Specifically, the behavior o
Externí odkaz:
http://arxiv.org/abs/2409.12356
Holographic multiple-input and multiple-output (MIMO) communications introduce innovative antenna array configurations, such as dense arrays and volumetric arrays, which offer notable advantages over conventional planar arrays with half-wavelength el
Externí odkaz:
http://arxiv.org/abs/2409.08080
The integration of Large Language Models (LLMs) into recommender systems has led to substantial performance improvements. However, this often comes at the cost of diminished recommendation diversity, which can negatively impact user satisfaction. To
Externí odkaz:
http://arxiv.org/abs/2408.12470
We pioneer a learning-based single-point prompt paradigm for infrared small target label generation (IRSTLG) to lobber annotation burdens. Unlike previous clustering-based methods, our intuition is that point-guided mask generation just requires one
Externí odkaz:
http://arxiv.org/abs/2408.08191