Zobrazeno 1 - 10
of 565
pro vyhledávání: '"ZHOU Mingyang"'
Autor:
Zhou Mingyang, Qiu Chengcheng
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
To address the problem of inaccurate positioning of new energy vehicles during cooperative detection, this paper investigates the positioning accuracy of different combinations of radar and infrared sensors. In order to meet the control requirements
Externí odkaz:
https://doaj.org/article/ab6b34130ed249b6821ddde03801a5ec
Predicting drug-drug interaction (DDI) plays an important role in pharmacology and healthcare for identifying potential adverse interactions and beneficial combination therapies between drug pairs. Recently, a flurry of graph learning methods have be
Externí odkaz:
http://arxiv.org/abs/2410.18583
Autor:
Liao, Hao, Zhang, Wei, Huang, Zhanyi, Long, Zexiao, Zhou, Mingyang, Wu, Xiaoqun, Mao, Rui, Yeung, Chi Ho
In the past decade, significant strides in deep learning have led to numerous groundbreaking applications. Despite these advancements, the understanding of the high generalizability of deep learning, especially in such an over-parametrized space, rem
Externí odkaz:
http://arxiv.org/abs/2407.20724
Autor:
Huang, Kung-Hsiang, Chan, Hou Pong, Fung, Yi R., Qiu, Haoyi, Zhou, Mingyang, Joty, Shafiq, Chang, Shih-Fu, Ji, Heng
Data visualization in the form of charts plays a pivotal role in data analysis, offering critical insights and aiding in informed decision-making. Automatic chart understanding has witnessed significant advancements with the rise of large foundation
Externí odkaz:
http://arxiv.org/abs/2403.12027
Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommender systems - systems that are conversational, explainable, and control
Externí odkaz:
http://arxiv.org/abs/2403.05063
Autor:
Huang, Kung-Hsiang, Zhou, Mingyang, Chan, Hou Pong, Fung, Yi R., Wang, Zhenhailong, Zhang, Lingyu, Chang, Shih-Fu, Ji, Heng
Recent advancements in large vision-language models (LVLMs) have led to significant progress in generating natural language descriptions for visual content and thus enhancing various applications. One issue with these powerful models is that they som
Externí odkaz:
http://arxiv.org/abs/2312.10160
Autor:
Zhou, Mingyang, Yan, Zichao, Layne, Elliot, Malkin, Nikolay, Zhang, Dinghuai, Jain, Moksh, Blanchette, Mathieu, Bengio, Yoshua
Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history and numerous applications notwithstanding, inference of phylogenetic trees from sequence data remains challengi
Externí odkaz:
http://arxiv.org/abs/2310.08774
Publikováno v:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2023
Explainable recommendation is a technique that combines prediction and generation tasks to produce more persuasive results. Among these tasks, textual generation demands large amounts of data to achieve satisfactory accuracy. However, historical user
Externí odkaz:
http://arxiv.org/abs/2306.12657
Building cross-model intelligence that can understand charts and communicate the salient information hidden behind them is an appealing challenge in the vision and language(V+L) community. The capability to uncover the underlined table data of chart
Externí odkaz:
http://arxiv.org/abs/2305.18641
In this paper, we present an algorithmic study on how to surpass competitors in popularity by strategic promotions in social networks. We first propose a novel model, in which we integrate the Preferential Attachment (PA) model for popularity growth
Externí odkaz:
http://arxiv.org/abs/2304.14971