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pro vyhledávání: '"Liang, Penghao"'
This article introduces the importance of machine learning in real-world applications and explores the rise of MLOps (Machine Learning Operations) and its importance for solving challenges such as model deployment and performance monitoring. By revie
Externí odkaz:
http://arxiv.org/abs/2405.09819
In addition to environmental perception sensors such as cameras, radars, etc. in the automatic driving system, the external environment of the vehicle is perceived, in fact, there is also a perception sensor that has been silently dedicated in the sy
Externí odkaz:
http://arxiv.org/abs/2404.04492
The integration of LLMOps into personalized recommendation systems marks a significant advancement in managing LLM-driven applications. This innovation presents both opportunities and challenges for enterprises, requiring specialized teams to navigat
Externí odkaz:
http://arxiv.org/abs/2404.00903
This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis. It begins by introducing the fundamental concept of sentiment analysis and how deep learning methods are utilized in this do
Externí odkaz:
http://arxiv.org/abs/2403.08217
With the boom of e-commerce and web applications, recommender systems have become an important part of our daily lives, providing personalized recommendations based on the user's preferences. Although deep neural networks (DNNs) have made significant
Externí odkaz:
http://arxiv.org/abs/2403.02760
In addressing the computational and memory demands of fine-tuning Large Language Models(LLMs), we propose LoRA-SP(Streamlined Partial Parameter Adaptation), a novel approach utilizing randomized half-selective parameter freezing within the Low-Rank A
Externí odkaz:
http://arxiv.org/abs/2403.08822
Autor:
Lu, Joan, Davidrajuh, Reggie, Wu, Yichao, Xiang, Yafei, Huo, Shuning, Gong, Yulu, Liang, Penghao
Publikováno v:
Proceedings of SPIE; June 2024, Vol. 13171 Issue: 1 p131711Z-131711Z-9, 1185409p
Publikováno v:
IOP Conference Series: Earth & Environmental Science; 2021, Vol. 859, p1-5, 5p
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Akademický článek
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