Výsledky vyhledávání - "Lin Rongrong"

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Computing the Proximal Operator of the $\ell_{1,q}$-norm for Group Sparsity

Autor: Lin, Rongrong, Chen, Shihai, Feng, Han, Liu, Yulan

In this note, we comprehensively characterize the proximal operator of the $\ell_{1,q}$-norm with $0\!<\!q\!<\!1$ by exploiting the well-known proximal operator of the $\ell_q$-norm on the real line. In particular, much more explicit characterization

Externí odkaz: http://arxiv.org/abs/2409.14156

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Akademický článek

Construction of Sensitive Thesaurus for Network Rumors——Taking the Microblog Rumors as an Example

Autor: Xia Song, Lin Rongrong, Liu Kan

Publikováno v: Zhishi guanli luntan, Vol 4, Iss 5, Pp 267-275 (2019)

[Purpose /significance] The network rumors seriously influent the spread of normal information on the internet. The purpose of this paper is to construct a sensitive lexicon on microblog rumors and to improve the recognition accuracy of the network r

Externí odkaz: https://doaj.org/article/9a71c27c6a404772bcbe2226a10400a5

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Akademický článek

Stance Detection in Chinese Microblogs

Autor: Liu Kan, Tian Ningmeng, Wang Hongyu, Lin Rongrong, Wang Demin

Publikováno v: Zhishi guanli luntan, Vol 2, Iss 3, Pp 175-185 (2017)

[Purpose/significance] The paper introduces a new approach to automatically detect stance in Chinese microblogs by building a serial combination model based on Sentiment Weighted Algorithm and Naive Bayes (SWNB model). [Method/process] Firstly, this

Externí odkaz: https://doaj.org/article/efc6976907d448c1b4ed5169335d3202

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On Choosing Initial Values of Iteratively Reweighted $\ell_1$ Algorithms for the Piece-wise Exponential Penalty

Autor: Lin, Rongrong, Li, Shimin, Liu, Yulan

Computing the proximal operator of the sparsity-promoting piece-wise exponential (PiE) penalty $1-e^{-|x|/\sigma}$ with a given shape parameter $\sigma>0$, which is treated as a popular nonconvex surrogate of $\ell_0$-norm, is fundamental in feature

Externí odkaz: http://arxiv.org/abs/2310.17849

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Kernel Support Vector Machine Classifiers with the $\ell_0$-Norm Hinge Loss

Autor: Lin, Rongrong, Yao, Yingjia, Liu, Yulan

Support Vector Machine (SVM) has been one of the most successful machine learning techniques for binary classification problems. The key idea is to maximize the margin from the data to the hyperplane subject to correct classification on training samp

Externí odkaz: http://arxiv.org/abs/2306.13991

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The Proximal Operator of the Piece-wise Exponential Function and Its Application in Compressed Sensing

Autor: Liu, Yulan, Zhou, Yuyang, Lin, Rongrong

This paper characterizes the proximal operator of the piece-wise exponential function $1\!-\!e^{-|x|/\sigma}$ with a given shape parameter $\sigma\!>\!0$, which is a popular nonconvex surrogate of $\ell_0$-norm in support vector machines, zero-one pr

Externí odkaz: http://arxiv.org/abs/2306.13425

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