no code implementations • 27 Nov 2024 • Lewen Yang, Xuanyu Zhou, Juao Fan, Xinyi Xie, Shengxin Zhu
Foundational models have the characteristics of pre-training, transfer learning, and self-supervised learning, and pre-trained models can be fine-tuned and applied to various downstream tasks.
no code implementations • 15 Oct 2024 • Zongyuan Han, Wenhao Li, Shengxin Zhu
In this paper, we investigate diagonal estimation for large or implicit matrices, aiming to develop a novel and efficient stochastic algorithm that incorporates adaptive parameter selection.
no code implementations • 12 Jul 2024 • Linhan Xia, Yicheng Yang, Ziou Chen, Zheng Yang, Shengxin Zhu
This study proposes a multi-modal movie recommendation system by extract features of the well designed posters for each movie and the narrative text description of the movie.
1 code implementation • 4 Jun 2024 • Yuda Wang, Xuxin He, Shengxin Zhu
EchoMamba4Rec leverages these control relationships in sequential recommendation and integrates bi-directional processing with frequency-domain filtering to capture complex patterns and dependencies in user interaction data more effectively.
1 code implementation • 30 Mar 2024 • Zhaofeng Zhang, Banghao Chen, Shengxin Zhu, Nicolas Langrené
In traditional quantitative trading practice, navigating the complicated and dynamic financial market presents a persistent challenge.
no code implementations • 23 Oct 2023 • Banghao Chen, Zhaofeng Zhang, Nicolas Langrené, Shengxin Zhu
This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs).
no code implementations • 17 Dec 2022 • Baode Gao, Guangpeng Zhan, Hanzhang Wang, Yiming Wang, Shengxin Zhu
Accurate prediction of users' responses to items is one of the main aims of many computational advising applications.
1 code implementation • 17 Aug 2022 • Binrui Shen, Qiang Niu, Shengxin Zhu
The advanced constraining operator enables a CSGO for large graph matching, which outperforms state-of-the-art methods in experiments.
no code implementations • 2 Mar 2021 • Xinliang Liu, Lei Zhang, Shengxin Zhu
In this paper, we demonstrate the construction of generalized Rough Polyhamronic Splines (GRPS) within the Bayesian framework, in particular, for multiscale PDEs with rough coefficients.
Numerical Analysis Numerical Analysis
no code implementations • 16 Jan 2020 • Binrui Shen, Qiang Niu, Shengxin Zhu
Fabricating experimental pictures in research work is a serious academic misconduct, which should better be detected in the reviewing process.
no code implementations • 2 Nov 2019 • Shengxin Zhu, Andrew J Wathen
Algorithms for Gaussian process, marginal likelihood methods or restricted maximum likelihood methods often require derivatives of log determinant terms.