陈雪

时间:2021-07-20浏览:2130

E-Mail: xuechen1989@ustc.edu.cn

个人主页:http://staff.ustc.edu.cn/~xuechen1989/   

英文详细简历:http://staff.ustc.edu.cn/~xuechen1989/cv.pdf

主要研究方向:随机算法和伪随机,大数据算法,机器学习理论,理论计算机和密码学基础


 陈雪,中国科学技术大学计算机学院特任教授。本科毕业于清华大学姚班,博士毕业于美国德克萨斯大学奥斯丁分校计算机系,师从 David Zuckerman。曾在美国西北大学任博士后研究员,美国乔治梅森大学任助理教授。主要的研究方向是理论计算机,包括随机算法和伪随机,大数据算法,机器学习理论和密码学基础。在STOC, FOCS, SODA, COLT等理论计算机科学的一流国际会议上发表论文十余篇。

 

招生信息

欢迎对大数据算法,机器学习理论,理论计算机,组合数学和应用概率论感兴趣的同学加入我们的科研小组。如果有感兴趣的课题,请发送邮件至 xuechen1989@ustc.edu.cn

 

代表性论著

  1. Xue Chen and Michal Derezinski. Query Complexity of Least Absolute Deviation Regression via Robust Uniform Convergence. In Conference on Learning Theory (COLT), to appear, 2021.

  2. Xue Chen, Anindya De, and Rocco A. Servedio. Testing Noisy Linear Functions for Sparsity. In ACM Symposium on Theory of Computing (STOC), pages 610--623, 2020.

  3. Pranjal Awasthi, Xue Chen, and Aravindan Vijayaraghavan. Estimating Principal Components under Adversarial Perturbations. In Conference on Learning Theory (COLT) PMLR 125:323--362, 2020.

  4. Xue Chen and Anindya De. Reconstruction under outliers for Fourier-sparse functions. In ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 2010--2029, 2020.

  5. Xue Chen and Eric Price. Active Regression via Linear-Sample Sparsification. In Conference on Learning Theory (COLT), PMLR 99:663--695, 2019.

  6. Xue Chen. Derandomized Balanced Allocation. In ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 2513--2526, 2019.

  7. Xue Chen, Daniel Kane, Eric Price, and Zhao Song. Fourier-sparse Interpolation without a Frequency gap. In Symposium on Foundations of Computer Science (FOCS), pages 741--750, 2016.