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pro vyhledávání: '"Li WeiHua"'
The widespread application of Electronic Health Records (EHR) data in the medical field has led to early successes in disease risk prediction using deep learning methods. These methods typically require extensive data for training due to their large
Externí odkaz:
http://arxiv.org/abs/2404.14815
The Grey Wolf Optimizer (GWO) is recognized as a novel meta-heuristic algorithm inspired by the social leadership hierarchy and hunting mechanism of grey wolves. It is well-known for its simple parameter setting, fast convergence speed, and strong op
Externí odkaz:
http://arxiv.org/abs/2404.06524
While preference-based recommendation algorithms effectively enhance user engagement by recommending personalized content, they often result in the creation of ``filter bubbles''. These bubbles restrict the range of information users interact with, i
Externí odkaz:
http://arxiv.org/abs/2404.04906
Autor:
Wang, Guan, Frederick, Rebecca, Duan, Jinglong, Wong, William, Rupar, Verica, Li, Weihua, Bai, Quan
In this paper, we delve into the rapidly evolving challenge of misinformation detection, with a specific focus on the nuanced manipulation of narrative frames - an under-explored area within the AI community. The potential for Generative AI models to
Externí odkaz:
http://arxiv.org/abs/2402.15525
Autor:
Li, Weihua, Cao, Wei
Let $\mathbb{F}_q$ denote the finite field of characteristic $p$ and order $q$. Let $\mathbb{Z}_q$ denote the unramified extension of the $p$-adic rational integers $\mathbb{Z}_p$ with residue field $\mathbb{F}_q$. Given two positive integers $m,n$,
Externí odkaz:
http://arxiv.org/abs/2310.15637
Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning model complexity. In this paper, we introduce time-frequency dual-path com
Externí odkaz:
http://arxiv.org/abs/2308.11053
In the realm of personalized recommendation systems, the increasing concern is the amplification of belief imbalance and user biases, a phenomenon primarily attributed to the filter bubble. Addressing this critical issue, we introduce an innovative i
Externí odkaz:
http://arxiv.org/abs/2307.02797
The rapid growth of information on the Internet has led to an overwhelming amount of opinions and comments on various activities, products, and services. This makes it difficult and time-consuming for users to process all the available information wh
Externí odkaz:
http://arxiv.org/abs/2306.05537
Publikováno v:
Anti-Corrosion Methods and Materials, 2024, Vol. 71, Issue 4, pp. 348-356.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ACMM-12-2023-2933
Aspect term extraction is a fundamental task in fine-grained sentiment analysis, which aims at detecting customer's opinion targets from reviews on product or service. The traditional supervised models can achieve promising results with annotated dat
Externí odkaz:
http://arxiv.org/abs/2303.00815