全校師生：
我校定于2020年7月1日舉辦研究生靈犀學術殿堂——王建軍報告會，現將有關事項通知如下：
1.報告會簡介
報告人：王建軍教授
時間：2020年7月1日（星期三） 15：00
地點：騰訊會議（會議號：274947281）
報告題目：Low-tubal-rank Tensor Analysis: Theory, Algorithms and Applications
內容簡介：This talk will share our two recent results on low-tubal-rank tensor analysis. (1) LRTR: we establish a regularized tensor nuclear norm minimization (RTNNM) model for low-tubal-rank tensor recovery (LRTR). Then, we initiatively define a novel tensor restricted isometry property (t-RIP) based on tensor singular value decomposition (t-SVD). Besides, our theoretical results show that any third-order tensor X∈R^(n_1×n_2×n_3 ) whose tubal rank is at most can stably be recovered from its as few as measurements with a bounded noise constraint via the RTNNM model, if the linear map obeys t-RIP .(2) TRPCA: by incorporating prior information including the column and row space knowledge, we investigate the tensor robust principal component analysis (TRPCA) problem based on t-SVD. We establish sufficient conditions to ensure that under significantly weaker incoherence assumptions than tensor principal components pursuit method (TPCP), our proposed Modified-TPCP solution perfectly recovers the low-tubal-rank and the sparse components with high probability, provided that the available prior subspace information is accurate. In addition, we present an efficient algorithm by modifying the alternating direction method of multipliers (ADMM) to solve the Modified-TPCP program. Numerical experiments show that the Modified-TPCP based on prior subspace information does allow us to recover under weaker conditions than TPCP. The application of color video and face denoising task suggests the superiority of the proposed method over the existing state-of-the-art methods.
2.歡迎各學院師生前來聽報告。報告會期間請關閉手機或將手機調至靜音模式。
黨委學生工作部
數學與統計學院
2020年6月24日
報告人簡介
王建軍，博士，西南大學教授（研究員），博士生導師，重慶市創新創業領軍人才，巴渝學者特聘教授，重慶市學術帶頭人，美國數學評論評論員，重慶數學會理事，重慶市統計學重點學科學術帶頭人。主要研究方向為：高維數據建模、機器學習（深度學習）、數據挖掘、壓縮感知、張量數據建模、函數逼近論等。在神經網絡復雜性和高維數據稀疏建模等方面有一定的學術積累。主持并完成國家自然科學基金4項（其中面上項目2項，青年項目2項），教育部科學技術重點項目1項，重慶市自然科學基金1項，主研5項國家自然、社會科學基金；現主持國家自然科學基金面上項目一項，參與國家重點基礎研究發展‘973’計劃一項，多次出席國際、國內重要學術會議，并做特邀報告20余次。已在IEEE Transactions on Pattern Analysis and Machine Intelligence、Applied and Computational Harmonic Analysis , Inverse Problems，Neural Networks, Signal Processing, IEEE Signal Processing letters, Journal of Computational and Applied Mathematics, Neurocomputing, IET Signal Processing, IET Communication,中國科學(A,F輯),數學學報,計算機學報,電子學報，數學年刊等專業期刊發表90余篇學術論文。《中國科學》(A,F輯), IEEE Trans. Signal Process, image Process. Neural Networks and learning system及IEEE等系列刊物，Signal Processing，Neural Networks，Pattern Recognization，中國科學（A,F），計算機學報，電子學報，數學學報等知名期刊審稿人。2018年，以第一完成人申報的階段性成果《復雜結構性高維數據稀疏建模的方法與算法應用》榮獲重慶市自然科學三等獎。
