Zobrazeno 1 - 10
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pro vyhledávání: '"WANG, Fang"'
Autor:
Guo, Taicheng, Liu, Chaochun, Wang, Hai, Mannam, Varun, Wang, Fang, Chen, Xin, Zhang, Xiangliang, Reddy, Chandan K.
Language agents have recently been used to simulate human behavior and user-item interactions for recommendation systems. However, current language agent simulations do not understand the relationships between users and items, leading to inaccurate u
Externí odkaz:
http://arxiv.org/abs/2410.19627
Multi-modal Entity Linking (MEL) is a fundamental component for various downstream tasks. However, existing MEL datasets suffer from small scale, scarcity of topic types and limited coverage of tasks, making them incapable of effectively enhancing th
Externí odkaz:
http://arxiv.org/abs/2410.18096
Autor:
Wang, Fang, Gacesa, Marko
This study extends the examination of the Efficient-Market Hypothesis in Bitcoin market during a five year fluctuation period, from September 1 2017 to September 1 2022, by analyzing 28,739,514 qualified tweets containing the targeted topic "Bitcoin"
Externí odkaz:
http://arxiv.org/abs/2409.15988
Malware visualization analysis incorporating with Machine Learning (ML) has been proven to be a promising solution for improving security defenses on different platforms. In this work, we propose an integrated framework for addressing common problems
Externí odkaz:
http://arxiv.org/abs/2409.14439
We propose and experimentally demonstrate an innovative stock index prediction method using a weighted optical reservoir computing system. We construct fundamental market data combined with macroeconomic data and technical indicators to capture the b
Externí odkaz:
http://arxiv.org/abs/2408.00652
Autor:
Liu, Zhe, Zhu, Xiliang, Han, Tong, Huang, Yuhao, Wang, Jian, Liu, Lian, Wang, Fang, Ni, Dong, Gou, Zhongshan, Yang, Xin
Mitral regurgitation (MR) is a serious heart valve disease. Early and accurate diagnosis of MR via ultrasound video is critical for timely clinical decision-making and surgical intervention. However, manual MR diagnosis heavily relies on the operator
Externí odkaz:
http://arxiv.org/abs/2407.21497
We develop here a novel transfer learning methodology called Profiled Transfer Learning (PTL). The method is based on the \textit{approximate-linear} assumption between the source and target parameters. Compared with the commonly assumed \textit{vani
Externí odkaz:
http://arxiv.org/abs/2406.00701
Publikováno v:
Data Intelligence, Vol 1, Iss 4, Pp 309-332 (2019)
For many government departments, uncertainty aversion is a source of barriers in the advancement of data openness. A more active response to potential risks is needed and necessitates an in-depth examination of risks related to open government data (
Externí odkaz:
https://doaj.org/article/cd64082e06bf4678ae73caacdf8658e6
Autor:
Zhang, Xue, Cao, Si-Yuan, Wang, Fang, Zhang, Runmin, Wu, Zhe, Zhang, Xiaohan, Bai, Xiaokai, Shen, Hui-Liang
Most recent multispectral object detectors employ a two-branch structure to extract features from RGB and thermal images. While the two-branch structure achieves better performance than a single-branch structure, it overlooks inference efficiency. Th
Externí odkaz:
http://arxiv.org/abs/2405.16038
Autor:
Wang, Fang, Xia, Zhihong
We study the homotopical minimal measures for positive definite autonomous Lagrangian systems. Homotopical minimal measures are action-minimizers in their homotopy classes, while the classical minimal measures (Mather measures) are action-minimizers
Externí odkaz:
http://arxiv.org/abs/2403.04452