羅敏楠

羅敏楠，女，博士，西安交通大學電子與信息學部副教授。

基本介紹

• 中文名：羅敏楠
• 畢業院校：清華大學
• 學位/學歷：博士
• 職業：教師
• 專業方向：機器學習與最佳化、社交網路分析、多模態數據融合
• 任職院校：西安交通大學電子與信息學部
• 職稱：副教授

個人經歷

西安交通大學電子與信息學部計算機系副教授，博士生導師。博士畢業於清華大學計算機系，美國卡耐基梅隆大學（CMU）博士後。

2017/04 ～，西安交通大學計算機科學與技術系，副教授

2014/07 ～2017/03，西安交通大學計算機科學與技術系，講師

2015/09 ～2016/10，美國卡耐基梅隆大學計算機學院，博士後

2012/09～2013/03，英國愛丁堡大學數學學院，訪問學生

2010/09～2014/07，清華大學計算機科學與技術系，博士

2003/09～2010/07，陝西師範大學數學與信息科學學院，本科及碩士

研究方向

機器學習與最佳化、社交網路分析、多模態數據融合等。

主講課程

《最佳化方法與基礎》，電信學院本科生課程，2017/2018春

學術成果

承擔和參與了多項國家自然科學基金項目，在AAAI、IJCAI、TNNLS、TCYB、TFS等人工智慧和數據挖掘領域頂級國際會議和期刊上發表學術論文二十餘篇。

科研項目

圖文混合跨媒體知識單元的模糊分類方法研究，國家自然科學基金——青年科學基金項目，主持

裝備預言項目，主持

多媒體複雜事件檢測研究，百度科研基金項目，主持

論文

Peng, Z., Luo, M., Li, J., Liu, H., Zheng, Q., ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks, InProceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.

Luo, M., Nie, F., Chang, X., Yang, Y., Hauptmann, A. G., & Zheng, Q., Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling, In Proceedings of the 31th Association for the Advancement of Artificial Intelligence (AAAI), 2017.

Liu, H., Zheng, Q., Luo, M., Zhang, D., Chang, X., & Deng, C., How Unlabeled Web Videos Help Complex Event Detection? In Proceedings ofthe 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.

Luo, M., Zhang, L., Nie, F., Chang, X., Qian, B., & Zheng, Q., Adaptive Semi-supervised Learning with Discriminative Least Squares Regression, InProceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.

Luo, M., Nie, F., Chang, X., Yang, Y., Hauptmann, A., & Zheng, Q., Avoiding Optimal Mean Robust PCA/2DPCA with Non-greedy L1-norm Maximization, InInProceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.

Luo, M., Zheng, Q., & Liu, J., Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier. InProceedings of ELM-2015.

Luo, M., Sun, F., & Liu, H., Sparse Fuzzy c-regression Models with Application to T-S Fuzzy Systems Identification. InProceedings of IEEE International Conference on Fuzzy Systems, 2014.

Luo, M., Sun, F., & Liu, H., A Dynamic T-S Fuzzy Systems Identification Algorithm based on Sparsity Regularization, InProceedings of IEEE International Symposium onIntelligent Control, 2012.

Sun, F., Yang, J., Luo, M., & Liu, H., Optimal Necessary Conditions for General SISO Mamdani Fuzzy Systems as Function Approximators within a Given Accuracy, InProceedings of IEEE International Conference on Fuzzy Systems, 2011.

Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, Deep Semisupervised Zero-Shot Learning with Maximum Mean Discrepancy, Neural computation, 2018

Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G Hauptmann, Qinghua Zheng, Adaptive Unsupervised Feature Selection with Structure Regularization,IEEE Transactions on Neural Networks and Learning Systems, 2018

Minnan Luo, Xiaojun Chang, Liqiang Nie, Yi Yang, Alexander G Hauptmann, Qinghua Zheng, An Adaptive Semi-supervised Feature Analysis for Video Semantic Recognition, IEEE Transactions on Cybernetics, 2018

Lingling Zhang, Minnan Luo, Zhihui Li, Feiping Nie, Huaxiang Zhang, Jun Liu, Qinghua Zheng, Large-Scale Robust Semi-supervised Classification, IEEE Transactions on Cybernetics, 2018.

Caixia Yan, Minnan Luo, Huan Liu, Zhihui Li, Qinghua Zheng, Top-k Multi-class SVM Using Multiple Features, 2018

Qichao Xu, Zhou Su, Qinghua Zheng, Minnan Luo, Bo Dong, Secure Content Delivery with Edge Nodes to Save Caching Resources for Mobile Users in Green Cities, IEEE Transactions on Industrial Informatics, 2018

Minnan Luo, Xiaojun Chang, Yi Yang, Liqiang Nie, Alexander G Hauptmann, Qinghua Zheng, Simple to Complex Cross-modal Learning to Rank, Computer Vision and Image Understanding, 2017

Minnan Luo, Xiaojun Chang, Yi Yang, Liqiang Nie, Alexander G Hauptmann, Qinghua Zheng, Avoiding Optimal Mean L21-Norm Maximization-Based Robust PCA for Reconstruction, Neural computation, 2017

Lingyun Song, Jun Liu, Minnan Luo, Buyue Qian, Kuan Yang, Sparse Relational Topical Coding on Multi-modal Data, Pattern Recognition, 2017

Minnan Luo, Lingling Zhang, Jun Liu, Jun Guo, Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, Neurocomputing, 2017

Caixia Yan, Minnan Luo, Wenhe Liu, Qinghua Zheng, Robust Dictionary Learning with Graph Regularization for Unsupervised Person Re-identification, Multimedia Tools and Applications, 2018

Lingyun Song, Minnan Luo, Jun Liu, Lingling Zhang, Buyue Qian, Max Haifei Li, Qinghua Zheng, Sparse Multi-modal Topical Coding for Image Annotation, Neurocomputing, 2016

Hengshan Zhang, Qinghua Zheng, Ting Liu, Zijiang Yang, Minnan Luo, Yu Qu, Improving Linguistic Pairwise Comparison Consistency via Linguistic Discrete Regions, IEEE Transactions on Fuzzy Systems, 2016

Minnan Luo, Fuchun Sun, Huaping Liu, Dynamic T‐S Fuzzy Systems Identification Based on Sparse Regularization, Asian Journal of Control, 2015

Minnan Luo, Fuchun Sun, Huaping Liu, Joint Block Structure Sparse Representation for Multi-input–multi-output (MIMO) T–S Fuzzy System Identification, IEEE Transactions on Fuzzy Systems, 2014

Minnan Luo, Fuchun Sun, Huaping Liu, Zhijun Li, A Novel T–S fuzzy Systems Identification with Block Structured Sparse Representation, Journal of the Franklin Institute, 2014

Minnan Luo, Fuchun Sun, Huaping Liu, Hierarchical Structured Sparse Representation for T–S Fuzzy Systems Identification, IEEE Transactions on Fuzzy Systems, 2013

Minnan Luo, Yongming Li, Fuchun Sun, Huaping Liu, A New Algorithm for Testing Diagnosability of Fuzzy Discrete Event Systems, Information Sciences, 2012

榮譽獎項

中國人工智慧學會優秀博士學位論文提名，中國人工智慧學會，2014

優秀博士畢業生，清華大學計算機系，2014

谷歌Anita Borg計算機學科女性獎學金，Google公司，2012