Qi Lei (雷琦)

Qi Lei UT Austin 

Email: leiqi at ices.utexas.edu

Website: http://users.ices.utexas.edu/~leiqi/

I am a final year Ph.D candidate at Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, working with Professor Alexandros G. Dimakis and Inderjit S. Dhillon. I am also a member of Center for Big Data Analytics and Wireless Networking & Communications Group. I'm visiting IAS for the Theoretical Machine Learning program from September to December this year. Prior to that, I was a Research Fellow at the Simons Institute for the Theory of Computing at UC Berkeley for the program on Foundations of Deep Learning.

My research interests are machine learning, deep learning and optimization. Specifically, I'm interested in developing provably efficient and robust algorithms for some fundamental machine learning problems.

I'm currently looking for postdoc positions starting fall 2020. (Curriculum Vitae, Github, Google Scholar)

News and Announcement

01/2020 Our paper is accepted to AISTATS 2020:

12/2019 Attending NeurIPS 2019 to present our following papers:

11/2019 I am invited to give a talk on Deep Generative models and Inverse Problems at the mini-symposium “Machine Learning for Solving Partial Differential Equations and Inverse Problems” of the 2nd Annual Meeting of the SIAM Texas-Louisiana Section in Dallas on Nov 2nd, 2019

10/2019 I am going to attend the Rising Stars 2019 at UIUC (An Academic Career Workshop for Women in EECS) from Oct 29th to Nov 1st, 2019

10/2019 New paper out: “Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls”

10/2019 New paper out: “SGD Learns One-Layer Networks in WGANs”

09/2019 I am participating the “Special Year on Optimization, Statistics, and Theoretical Machine Learning” as a short-term visitor at the Institute of Advanced Study from September to December, 2019

09/2019 Two papers accepted to NeurIPS 2019

05/2019 I received Simons-Berkeley fellowship in Foundations of Deep Learning, 2019.

04/2019 Our sysML paper on paraphrasing attacks “Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification” was covered by Nature Story, VectureBeat, and TechTalks (code, slides)

Selected Papers

(full publication list)

6. Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis. “SGD Learns One-Layer Networks in WGANs”, arxiv preprint

5. Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S Dhillon, Alexandros G Dimakis. “Primal-Dual Block Frank-Wolfe”, Proc. of Neural Information Processing Systems (NeurIPS) 2019 (slides, code)

4. Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis. “Inverting Deep Generative models, One layer at a time”, Proc. of Neural Information Processing Systems (NeurIPS) 2019 (poster, code)

3. Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock. “Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification”, Systems and Machine Learning (sysML). 2019 (code, slides)

2. Qi Lei, Enxu Yan, Chao-yuan Wu, Pradeep Ravikumar, Inderjit Dhillon, “Doubly Greedy Primal-Dual Coordinate Methods for Sparse Empirical Risk Minimization”, Proc. of International Conference of Machine Learning (ICML), 2017 (code)

1. Rashish Tandon, Qi Lei, Alexandros G. Dimakis, Nikos Karampatziakis, “Gradient Coding: Avoiding Stragglers in Distributed Learning”, Proc. of International Conference of Machine Learning (ICML), 2017 (code)