徐林莉


E- mail：linlixu@ustc.edu.cn

個人主頁：http://staff.ustc.edu.cn/~linlixu/ 


主要研究方向：機器學習(Machine Learning)，數據挖掘(Data Mining)。


徐林莉，女，博士，教授。2002年畢業於中國科學技術大學計算機科學與技術係，獲學士學位；2007年於加拿大滑鐵盧大學(University of Waterloo)計算機學院獲得博士學位。

研究著重於從複雜的數據中學習有價值的信息，利用數學建模發展相應的算法。研究課題包括各種聚類(Clustering)算法，非監督學習(Unsupervised Learning)以及半監督學習(Semi-supervised Learning)，支持向量機(Support Vector Machines)及其相關的擴展，凸優化算法(Convex Programming)在機器學習中的應用等。在人工智能/機器學習領域頂級國際會議中發表論文多篇。


獲獎情況：

ICML2009年度最佳論文優秀獎。


代表性論著：

  1. Linli Xu, Martha White and Dale Schuurmans. Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning. In Proceedings of the 26th International Conference on Machine Learning (ICML-09), pages 1137-1144. Best Paper Award Honorable Mention.

  2. Linli Xu, Wenye Li and Dale Schuurmans. Fast Normalized Cut with Linear Constraints. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR-09), pages 2866-2873.

  3. Linli Xu. Convex Large Margin Training Techniques for Unsupervised, Semi-supervised, and Robust Support Vector Machines. Ph.D. Thesis, School of Computer Science, University of Waterloo, 2007.

  4. [4]Linli Xu, Koby Crammer and Dale Schuurmans. Robust Support Vector Machine Training via Convex Outlier Ablation. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-06), pages 536-542.

  5. Linli Xu, Dana Wilkinson, Finnegan Southey and Dale Schuurmans. Discriminative Unsupervised Learning of Structured Predictors. In Proceedings of the 23rd International Conference on Machine Learning (ICML-06), pages 1057-1064.

  6. Linli Xu and Dale Schuurmans. Unsupervised and Semi-supervised Multi-class Support Vector Machines. In Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-05), pages 904-910.

  7. Linli Xu, James Neufeld, Bryce Larson and Dale Schuurmans. Maximum Margin Clustering. In Advances in Neural Information Processing Systems (NIPS-04), pages 1537-1544.

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