CONVERGENCE_ANALYSIS

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Gradient sparsification for efficient wireless federated learning with differential privacy
《Science China(Information Sciences)》2024年第4期268-284,共17页Kang WEI Jun LI Chuan MA Ming DING Feng SHU Haitao ZHAO Wen CHEN Hongbo ZHU 
supported in part by National Natural Science Foundation of China(Grant Nos.62071296,62002170,62071234,U22A2002);National Key Research and Development Program of China(Grant No.2020YFB1807700);Fundamental Research Funds for the Central Universities(Grant No.30921013104);Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)(Grant Nos.BE2023022,BE2023022-2);Future Network Grant of Provincial Education Board in Jiangsu;Major Science and Technology Plan of Hainan Province(Grant No.ZDKJ2021022);Scientific Research Fund Project of Hainan University(Grant No.KYQD(ZR)-21008);Youth Foundation Project of Zhejiang Lab(Grant No.K2023PD0AA01);Collaborative Innovation Center of Information Technology,Hainan University(Grant No.XTCX2022XXC07);Sciences and Technology Commission of Shanghai Municipality(Grant Nos.22JC1404000,20JC1416502,PKX2021-D02)。
Federated learning(FL)enables distributed clients to collaboratively train a machine learning model without sharing raw data with each other.However,it suffers from the leakage of private information from uploading mo...
关键词：federated learning differential privacy gradient sparsification Lyapunov drift convergence analysis 
A convergence algorithm for graph co-regularized transfer learning
《Science China(Information Sciences)》2023年第3期146-155,共10页Zuyuan YANG Naiyao LIANG Zhenni LI Shengli XIE 
supported in part by Key-Area Research and Development Program of Guangdong Province(Grant No.2019B010121001);National Natural Science Foundation of China(Grant Nos.61722304,61803096);Guangdong Natural Science Foundation(Grant No.2022A1515010688).
Transfer learning is an important technology in addressing the problem that labeled data in a target domain are difficult to collect using extensive labeled data from the source domain.Recently,an algorithm named grap...
关键词：transfer learning convergence analysis non-negative matrix factorization multiplicative update algorithm optimization 
Dynamic network embedding via incremental skip-gram with negative sampling被引量：4
《Science China(Information Sciences)》2020年第10期85-103,共19页Hao PENG Jianxin LI Hao YAN Qiran GONG Senzhang WANG Lin LIU Lihong WANG Xiang REN 
supported by National Key R&D Program of China(Grant No.2016YFB1000103);National Natural Science Foundation of China(Grant Nos.61872022,61772151,61421003,SKLSDE-2018ZX-16)。
Network representation learning,as an approach to learn low dimensional representations of vertices,has attracted considerable research attention recently.It has been proven extremely useful in many machine learning t...
关键词：dynamic network embedding bound and convergence analysis multi-label classification link prediction 
A convergence analysis for a class of practical variance-reduction stochastic gradient MCMC被引量：3
《Science China(Information Sciences)》2019年第1期64-76,共13页Changyou CHEN Wenlin WANG Yizhe ZHANG Qinliang SU Lawrence CARIN 
Stochastic gradient Markov chain Monte Carlo(SG-MCMC) has been developed as a flexible family of scalable Bayesian sampling algorithms. However, there has been little theoretical analysis of the impact of minibatch si...
关键词：MARKOV CHAIN MONTE Carlo SG-MCMC variance REDUCTION deep neural networks 
Convergence analysis of ILC input sequence for underdetermined linear systems被引量：1
《Science China(Information Sciences)》2017年第9期282-284,共3页Dong SHEN Jian HAN Youqing WANG 
supported by National Natural Science Foundation of China(Grant Nos.61673045,61304085,61374099;Beijing Natural Science Foundation(Grant No.4152040)
Dear editor, Iterative learning control （ILC） is a kind of intelli- gent control strategy, applied to those systems that could complete a given task over a finite time inter- val and repeat it agMn and again. Since ...
关键词：In Convergence analysis of ILC input sequence for underdetermined linear systems ILC 
A junction-by-junction feedback-based strategy with convergence analysis for dynamic traffic assignment被引量：2
《Science China(Information Sciences)》2016年第1期27-43,共17页Tengfei LIU Xuesong LU Zhong-Ping JIANG 
supported in part by National Science Foundation(Grant Nos.DMS-0906659;ECCS-1230040);National Natural Science Foundation of China(Grant No.61374042);Fundamental Research Funds for the Central Universities in China(Grant Nos.N130108001;N140805001);State Key Laboratory of Intelligent Control and Decision of Complex Systems
By considering the traffic assignment problem as a control problem, this paper develops a new real- time route guidance strategy for accurate convergence of the traffic flows to user equilibrium （UE） or system optim...
关键词：dynamic traffic assignment user equilibrium （UE） system optimum （SO） CONVERGENCE LaSalle＇sinvariance principle 
Convergence analysis and application of the central force optimization algorithm
《Science China(Information Sciences)》2015年第5期204-206,共3页MENG Chao GONG Jing LIU SanMin SUN ZhiXin 
supported by National Natural Science Foundation of China(Grant Nos.61373135,61170276,61402240);Key University Science Research Project of Jiangsu Province(Grant No.12KJA520003);Science and Technology Enterprises Innovation Fund Project of Jiangsu Province(Grant No.BC2013027);Project for Production Study&Research of Jiangsu Province(Grant No.BY2013011);Introduction of Talent Scientific Research Fund of Nanjing University of Posts and Telecommunications(Grant No.NY214024);Natural Science Foundation of Jiangsu Province of China(Grant No.BK20140883)
Citation Meng C, Gong J, Li S M, et ah Convergence analysis and application of the central force optimization algorithm. Sci China InfSci, 2015, 58： 059301（3）, doi： 10.1007/s11432-015-5301-2
关键词：CFO Convergence analysis and application of the central force optimization algorithm 
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