Xiang WANG

I am currently a third year Ph.D. student at Duke University, in the Computer Science Department. I am fortunate to have Prof. Rong Ge as my advisor. Broadly, I am interested in deep learning theory. I did my undergraduate study at Shanghai Jiao Tong University (SJTU). In fall 2019, I visited IAS for the Special Year on Optimization, Statistics, and Theoretical Machine Learning. In Spring 2017, I did an intern in the Division of Mathematical Sciences, Nanyang Technological University, advised by Prof. Xiaohui Bei. At SJTU, I was conducting research on algorithmic game theory under the supervision of Prof. Fan Wu. Here is my CV (last update: Nov. 2019) Email: xwang AT cs DOT duke DOT edu Office: LSRC D125

Publications

• Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, Rong Ge.
  Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. NeurIPS 2019 [arXiv][blog]
  

• Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang*.
  Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. COLT 2019 [arXiv][poster][slides]
  

• Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang*.
  Learning Two-layer Neural Networks with Symmetric Inputs. ICLR 2019 [arXiv][poster]
  

• Chaoli Zhang, Xiang Wang, Fan Wu and Xiaohui Bei.
  Efficient Auctions with Identity-Dependent Negative Externalities. AAMAS 2018 (Short Paper)
  

• Xiang Wang, Zhenzhe Zheng, Fan Wu, Xiaoju Dong, Shaojie Tang and Guihai Chen.
  Strategy-proof Data Auctions with Negative Externalities. AAMAS 2016 (Short Paper)
  

Talks

• Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization.
  COLT 2019, Jun 2019.

Teaching

• CS630: Randomized Algorithms, Spring 2018. TA
• CS330: Algorithm Design, Fall 2018. TA

Awards

• Outstanding Ph.D. Research Initiation Project Award, Duke University (Sep. 2019)
• Outstanding Graduate Award, Shanghai Jiao Tong University (Jun. 2017)
• Elite Collegiate Award, China Computer Federation (Oct. 2016)

Service

• Journal refereeing: Journal of Machine Learning Research
• Conference refereeing: STOC, ICML, NeurIPS, COLT