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數(shù)學(xué)與信息科學(xué)學(xué)院學(xué)術(shù)報(bào)告:SLRTA: A Sparse and Low-Rank Tensor-based Approach to Internet Traffic Anomaly Detection Lyapunov stability versus Jacobi stability

作者:     編輯:科技處     來(lái)源:   發(fā)表于: 2021-03-16 09:27  點(diǎn)擊:
學(xué)術(shù)活動(dòng)日期 3月16日 時(shí)間 8:30-11:30
主講人 羅自炎,教授,北京交通大學(xué) 地址 騰訊會(huì)議(ID:882 713 363)

學(xué)術(shù)報(bào)告

題目:SLRTA: A Sparse and Low-Rank Tensor-based Approach to Internet Traffic Anomaly Detection Lyapunov stability versus Jacobi stability

報(bào)告人:羅自炎,教授,北京交通大學(xué)

地點(diǎn):騰訊會(huì)議(ID882 713 363

時(shí)間:2021316日,8:30-11:30

摘要:Internet traffic anomaly detection (ITAD) is a critical task for various network tasks such as traffic engineering and network security. Traditional matrix-based approaches of ITAD have limitations for traffic data with multi-way structures, while the emerging tensor-based approaches of ITAD lack of sufficient consideration for circumstances including incomplete measurements or link-load measurements. To address these issues, we formulate ITAD by a sparse low-rank tensor optimization model, taking into full consideration the intrinsic and potential properties including the sparsity of anomalies, the low-rankness and temporal stability and periodicity of the normal traffic data. Although the resulting optimization model is non-convex and discontinuous due to the involved L0-norm and the tensor rank function, optimality analysis via stationarity is established, based on which an efficient proximal gradient method with theoretical convergence to stationary points is designed. Numerical experiments on Internet traffic trace data Abilene and GEANT demonstrate the high efficiency of our proposed sparse and low-rank tensor-based approach (SLRTA) for ITAD.

報(bào)告人簡(jiǎn)介

  羅自炎,女,北京交通大學(xué)理學(xué)院教授、博士生導(dǎo)師。2010年獲北京交通大學(xué)理學(xué)院運(yùn)籌學(xué)與控制論專(zhuān)業(yè)博士學(xué)位,美國(guó)Stanford大學(xué)管理與科學(xué)工程系、新加坡國(guó)立大學(xué)、英國(guó)南安普頓大學(xué)訪(fǎng)問(wèn)學(xué)者、香港理工大學(xué)應(yīng)用數(shù)學(xué)系研究助理。主要從事大規(guī)模統(tǒng)計(jì)優(yōu)化算法設(shè)計(jì)、稀疏與低秩優(yōu)化、張量分析與張量理論等方面的研究。共發(fā)表SCI檢索期刊論文30余篇,其中ESI高被引論文2篇。撰寫(xiě)英文專(zhuān)著1部,由國(guó)際著名SIAM出版社于20174月出版,編寫(xiě)中文著作《半定規(guī)劃》, 已被國(guó)內(nèi)多所高校的優(yōu)化專(zhuān)業(yè)選為研究生教材。主持國(guó)家自然科學(xué)基金面上項(xiàng)目、國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目子課題、國(guó)家自然科學(xué)基金青年基金項(xiàng)目、北京市自然科學(xué)基金重點(diǎn)項(xiàng)目各1項(xiàng)。2016年在北京運(yùn)籌學(xué)年會(huì)上做大會(huì)特邀報(bào)告,2017年在第十一屆全國(guó)數(shù)學(xué)規(guī)劃學(xué)術(shù)會(huì)議上做青年專(zhuān)題報(bào)告,2020年獲中國(guó)運(yùn)籌學(xué)會(huì)青年科技獎(jiǎng)提名獎(jiǎng)。

編輯:科技處

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