检索结果-内蒙古大学图书馆

SOLVING OPTIMIZATION PROBLEMS OVER THE STIEFEL MANIFOLD BY SMOOTH EXACT PENALTY FUNCTIONS

Journal of Computational Mathematics 2024年第5期42卷 1246-1276页

作者： Nachuan Xiao Xin Liu The Institute of Operations Research and Analytics National University of SingaporeSingapore State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of Sciencesand University of Chinese Academy of SciencesChina

In this paper,we present a novel penalty model called ExPen for optimization over the Stiefel *** from existing penalty functions for orthogonality constraints,ExPen adopts a smooth penalty function without using any first-order derivative of the objective *** show that all the first-order stationary points of ExPen with a sufficiently large penalty parameter are either feasible,namely,are the first-order stationary points of the original optimization problem,or far from the Stiefel ***,the original problem and ExPen share the same second-order stationary ***,the exact gradient and Hessian of ExPen are easy to *** a consequence,abundant algorithm resources in unconstrained optimization can be applied straightforwardly to solve ExPen.

关键词： Orthogonality constraint Stiefel manifold Penalty function

来源：评论

学校读者我要写书评

暂无评论

IP-geolocater:a more reliable IP geolocation algorithm based on router error training

引用

Frontiers of Computer science 2022年第1期16卷 101-111页

作者： Shuodi ZU Xiangyang LUO Fan ZHANG State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China Zhengzhou Science and Technology Institute Zhengzhou450001China

Location based services(LBS)are widely utilized,and determining the location of users’IP is the foundation for *** by unstable delay and insufficient landmarks,the existing geolocation algorithms have problems such as low geolocation accuracy and uncertain geolocation error,difficult to meet the requirements of LBS for accuracy and reliability.A new IP geolocation algorithm based on router error training is proposed in this manuscript to improve the accuracy of geolocation results and obtain the current geolocation error ***,bootstrapping is utilized to divide the landmark data into training set and verification set,and/24 subnet distribution is utilized to extend the training ***,the path detection is performed on nodes in the three data sets respectively to extract the metropolitan area network(MAN)of the target city,and the geolocation result and error of each router in MAN are obtained by training the detection ***,the MAN is utilized to get the target’s *** on China’s 24,254 IP geolocation experiments,the proposed algorithm has higher geolocation accuracy and lower median error than existing typical geolocation algorithms LBG,SLG,NNG and RNBG,and in most cases the difference is less than 10km between estimated error and actual error.

关键词： estimated error geolocation path detection network measurement

来源：评论

学校读者我要写书评

暂无评论

A survey on textual emotion cause extraction in social networks

引用

Digital Communications and Networks 2025年第2期11卷 524-536页

作者： Sancheng Peng Lihong Cao Guojun Wang Zhouhao Ouyang Yongmei Zhou Shui Yu Laboratory of Language Engineering and Computing Center for Linguistics and Applied Linguistics Guangdong University of Foreign Studies School of English Education Guangdong University of Foreign Studies School of Computer Science and Cyber Engineering Guangzhou University South China University of Technology School of Information Science and Technology Guangdong University of Foreign Studies School of Computer Science University of Technology Sydney

With the rapid development of web technology, Social Networks(SNs) have become one of the most popular platforms for users to exchange views and to express their emotions. More and more people are used to commenting on a certain hot spot in SNs, resulting in a large amount of texts containing emotions. Textual Emotion Cause Extraction(TECE) aims to automatically extract causes for a certain emotion in texts, which is an important research issue in natural language processing. It is different from the previous tasks of emotion recognition and emotion classification. In addition, it is not limited to the shallow-level emotion classification of text, but to trace the emotion source. In this paper, we provide a survey for TECE. First, we introduce the development process and classification of TECE. Then, we discuss the existing methods and key factors for TECE. Finally, we enumerate the challenges and developing trend for TECE.

关键词： Text Emotion Emotion cause Machine learning Deep learning

来源：评论

学校读者我要写书评

暂无评论

Cooperative Target Tracking of Multiple Autonomous Surface Vehicles Under Switching Interaction Topologies

引用

IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 673-684页

作者： Lang Ma Yu-Long Wang Qing-Long Han Shanghai Key Laboratory of Power Station Automation Technology and the School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia IEEE

This paper is concerned with the cooperative target tracking of multiple autonomous surface vehicles(ASVs)under switching interaction *** the target to be tracked,only its position can be measured/received by some of the ASVs,and its velocity is unavailable to all the ASVs.A distributed extended state observer taking into consideration switching topologies is designed to integrally estimate unknown target dynamics and neighboring ASVs'***,a novel kinematic controller is designed,which takes full advantage of known information and avoids the approximation of some virtual control ***,a disturbance observer is presented to estimate unknown time-varying environmental ***,a distributed dynamic controller is designed to regulate the involved ASVs to cooperatively track the *** enables each ASV to adjust its forces and moments according to the received information from its *** effectiveness of the derived results is demonstrated through cooperative target tracking performance analysis for a tracking system composed of five interacting ASVs.

关键词： Autonomous surface vehicles(ASVs) cooperative target tracking distributed extended state observer switching topologies

来源：评论

学校读者我要写书评

暂无评论

A clustering and generative adversarial networks-based hybrid approach for imbalanced data classification

引用

Journal of Ambient Intelligence and Humanized computing 2023年第6期14卷 8003-8018页

作者： Ding, Hongwei Cui, Xiaohui School of Cyber Science and Engineering Wuhan University Wuhan China Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan University Wuhan China

Imbalanced data often exists in related fields such as banking, insurance, security and medical care. The imbalanced distribution of data will lead to the deviation of decision-making, making it easy for a small number of samples to be divided incorrectly. Therefore, as a challenging task, imbalanced data classification has attracted extensive research in many disciplines. In this study, we propose a method based on the combination of clustering and generative adversarial network (GAN) to deal with the problem of imbalanced data classification. Firstly, we divide the majority class samples into three types according to the K-nearest neighbor algorithm. Secondly, undersampling is performed on the three types of data in the majority class through the clustering method. Then, a GAN model for tabular data generation is designed for oversampling of minority class samples. Finally, the preprocessed majority and minority data are used to train the machine learning model. We used real-world data sets to conduct relevant test experiments. The experimental results show that the imbalanced data processed by the method in this paper have achieved excellent results in the two evaluation indicators of the three common classification methods. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Generalize Audio Deepfake Algorithm Recognition via Attribution Enhancement

Generalize Audio Deepfake Algorithm Recognition via Attribut...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wang, Zhigang Ye, Dengpan Li, Jingyang Deng, Jiacheng Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9798350368741

The development of voice cloning techniques has made forgery audios indistinguishable, posing an urgency to trace their sources. Many existing works focus on improving identification accuracy for audio deepfake algorithm recognition. However, most methods ignore the impact of complex information in audio signals on attribution. In this paper, we propose an audio deepfake attribution enhancement (ADAE) strategy, which aims to magnify the fingerprints of generation styles by removing the speaker information. This is achieved through an information disentangle block with an extra speaker encoder. In addition, we propose the FakeSource dataset, a novel audio deepfake algorithm recognition dataset that contains 25 different voice cloning algorithms, to address the constraint of data scarcity. Experiments on the FakeSource dataset demonstrate that ADAE improves the performance of unseen algorithm detection. We also assess ADAE on a more challenging training-free task which shows competitive performance. © 2025 IEEE.

关键词： Audio deepfake algorithm recognition feature enhancement representation disentangle

来源：评论

学校读者我要写书评

暂无评论

Applications and potentials of machine learning in optoelectronic materials research:An overview and perspectives

引用

Chinese Physics B 2023年第12期32卷 108-128页

作者：张城洲付小倩 School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network based Intelligent Computing University of JinanJinan 250022China

Optoelectronic materials are essential for today's scientific and technological development,and machine learning provides new ideas and tools for their *** this paper,we first summarize the development history of optoelectronic materials and how materials informatics drives the innovation and progress of optoelectronic materials and ***,we introduce the development of machine learning and its general process in optoelectronic materials and describe the specific implementation *** focus on the cases of machine learning in several application scenarios of optoelectronic materials and devices,including the methods related to crystal structure,properties(defects,electronic structure)research,materials and devices optimization,material characterization,and process *** summarizing the algorithms and feature representations used in different studies,it is noted that prior knowledge can improve optoelectronic materials design,research,and decision-making ***,the prospect of machine learning applications in optoelectronic materials is discussed,along with current challenges and future *** paper comprehensively describes the application value of machine learning in optoelectronic materials research and aims to provide reference and guidance for the continuous development of this field.

关键词： optoelectronic materials devices machine learning prior knowledge

来源：评论

学校读者我要写书评

暂无评论

Density estimation-based method to determine sample size for random sample partition of big data

引用

Frontiers of Computer science 2024年第5期18卷 57-70页

作者： Yulin HE Jiaqi CHEN Jiaxing SHEN Philippe FOURNIER-VIGER Joshua Zhexue HUANG Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518107China College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Computing and Decision Sciences Lingnan UniversityHong Kong 999077China

Random sample partition(RSP)is a newly developed big data representation and management model to deal with big data approximate computation *** research and practical applications have confirmed that RSP is an efficient solution for big data processing and ***,a challenge for implementing RSP is determining an appropriate sample size for RSP data *** a large sample size increases the burden of big data computation,a small size will lead to insufficient distribution information for RSP data *** address this problem,this paper presents a novel density estimation-based method(DEM)to determine the optimal sample size for RSP data ***,a theoretical sample size is calculated based on the multivariate Dvoretzky-Kiefer-Wolfowitz(DKW)inequality by using the fixed-point iteration(FPI)***,a practical sample size is determined by minimizing the validation error of a kernel density estimator(KDE)constructed on RSP data blocks for an increasing sample ***,a series of persuasive experiments are conducted to validate the feasibility,rationality,and effectiveness of *** results show that(1)the iteration function of the FPI method is convergent for calculating the theoretical sample size from the multivariate DKW inequality;(2)the KDE constructed on RSP data blocks with sample size determined by DEM can yield a good approximation of the probability density function(p.d.f);and(3)DEM provides more accurate sample sizes than the existing sample size determination methods from the perspective of *** demonstrates that DEM is a viable approach to deal with the sample size determination problem for big data RSP implementation.

关键词： random sample partition big data sample size Dvoretzky-Kiefer-Wolfowitz inequality kerneldensity estimator probability density function

来源：评论

学校读者我要写书评

暂无评论

Decision making framework for heterogeneous QoS information: an application to cloud service selection

引用

Journal of Ambient Intelligence and Humanized computing 2023年第3期14卷 2915-2934页

作者： Tiwari, Rohit Kumar Kumar, Rakesh Baranwal, Gaurav Buyya, Rajkumar Department of Computer Science and Engineering Madan Mohan Malaviya University of Technology Gorakhpur273010 India Department of Computer Science BHU Varanasi India Cloud Computing and Distributed Systems Laboratory School of Computing and Information Systems University of Melbourne Melbourne Australia

In recent times, appropriate decision-making in challenging and critical situations has been very well supported by multicriteria decision-making (MCDM) methods. The technique for order of preference by similarity to ideal solution (TOPSIS) is the most widely used MCDM method for solving decision problems. However, it restricts decision-makers to use only one type of Quality of Service (QoS) information, and it suffers from the rank reversal problem. Restriction to only one type of QoS makes the decision problems more challenging, as it restricts the decision-makers freedom. Further, the rank reversal problem makes the decision result unreliable. To address these issues of TOPSIS, we have proposed a reliable rank reversal robust modular TOPSIS (RMo-TOPSIS). RMo-TOPSIS allows crisp, interval, fuzzy, intuitionistic and neutrosophic fuzzy QoS metrics. It does not suffer from the rank reversal problem. Cloud computing provides computing services on-demand basis without involving maintenance by its users. The availability of many cloud service providers and their services makes cloud service selection a challenging problem. To validate RMo-TOPSIS, we select the cloud service selection consisting of different types of QoS metrics as an application. Experiments on cloud service selection show consistency and accuracy in results obtained by RMo-TOPSIS and its robustness against rank reversal. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

A Novel Construction of Two-Dimensional Z-Complementary Array Code Sets Based on Extended Boolean Functions

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 7821-7834页

作者： Tian, Liying Song, Xiaoshi Li, Yubo Zhang, Haijun Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China Yanshan University School of Information Science and Engineering Qinhuangdao066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao066004 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

Two-dimensional (2-D) array sets with good 2-D correlation properties have received considerable attention in wireless communication systems. This paper focuses on 2-D Z-complementary array code sets (ZCACSs), which have ideal 2-D correlation properties within a rectangular zone around the origin. By developing a theory linking 2-D extended Boolean functions with 2-D arrays, we establish an efficient construction of 2-D ZCACSs. In contrast to previous work, the proposed construction is capable of producing 2-D ZCACSs with new flexible parameters. Constructions of three-dimensional (3-D) and higher-dimensional ZCACSs are further investigated. We remark that 2-D and higher-dimensional complete complementary codes (CCCs) can also be generated from the proposed constructions. © 1967-2012 IEEE.

关键词： Codes (symbols)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：