Publication List

Publications

29. Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit Dhillon, Cho-Jui Hsieh ‘‘Cat: Customized adversarial training for improved robustness", to appear at IJCAI 2022

28. Baihe Huang*, Kaixuan Huang*, Sham M. Kakade*, Jason D. Lee*, Qi Lei*, Runzhe Wang*, Jiaqi Yang* ‘‘Optimal Gradient-based Algorithms for Non-concave Bandit Optimization", NeurIPS 2021

27. Baihe Huang*, Kaixuan Huang*, Sham M. Kakade*, Jason D. Lee*, Qi Lei*, Runzhe Wang*, Jiaqi Yang* ‘‘Going Beyond Linear RL: Sample Efficient Neural Function Approximation, NeurIPS 2021

26. Kurtland Chua, Qi Lei, Jason D. Lee, ‘‘How fine-tuning allows for effective meta-learning", NeurIPS 2021

25. Jason D Lee*, Qi Lei*, Nikunj Saunshi*, Jiacheng Zhuo*, ‘‘Predicting What You Already Know Helps: Provable Self-Supervised Learning", NeurIPS 2021

24. Tianle Cai*, Ruiqi Gao*, Jason D Lee*, Qi Lei*. ‘‘A Theory of Label Propagation for Subpopulation Shift", ICML 2021

23. Qi Lei, Wei Hu, Jason D. Lee. ‘‘Near-Optimal Linear Regression under Distribution Shift", ICML 2021

22. Jay Whang, Qi Lei, Alexandros G. Dimakis. “Solving Inverse Problems with a Flow-based Noise Model”, ICML 2021

21. Qi Lei*, Sai Ganesh Nagarajan*, Ioannis Panageas*, Xiao Wang*. “Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes”, AISTATS 2021

20. Simon S. Du*, Wei Hu*, Sham M. Kakade*, Jason D. Lee*, Qi Lei*. “Few-Shot Learning via Learning the Representation, Provably”, ICLR 2021

19. Xiao Wang, Qi Lei, Ioannis Panageas. “Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev”, Proc. of Neural Information Processing Systems (NeurIPS), 2020

18. Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis. “SGD Learns One-Layer Networks in WGANs”, Proc. of International Conference of Machine Learning (ICML) 2020

17. Jiacheng Zhuo, Qi Lei, Alexandros G. Dimakis, Constantine Caramanis. “Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls”, AISTATS 2020

16. 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, poster, code)

15. 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)

14. Qi Lei, Jinfeng Yi, Roman Vaculin, Lingfei Wu, Inderjit Dhillon. “Similarity Preserving Representation Learning for Time Series Analysis”, The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (code)

13. 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)

12. Jinfeng Yi, Qi Lei, Wesley Gifford, Ji Liu. “Negative-Unlabeled Tensor Factorization for Location Category Inference from Inaccurate Mobility Data”, SIAM International Conference on Data Mining (SDM), 2019 (code)

11. Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney. “Hessian-based Analysis of Large Batch Training and Robustness to Adversaries”, Neural Information Processing Systems (NIPS), 2018

10. Jiong Zhang, Qi Lei, Inderjit Dhillon, “Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization”, International Conference of Machine Learning (ICML), July. 2018

9. Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei and Michael Witbrock, “Random Warping Series: A Random Features Method for Time-Series Embedding”, Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS), 2018

8. Hsiang-fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit Dhillon, “A Greedy Approach for Budgeted Maximum Inner Product Search”, Proc. of Neural Information Processing Systems (NIPS), 2017

7. 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)

6. 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)

5. Qi Lei, Kai Zhong, Inderjit. Dhillon, “Coordinate-wise Power Method”, Proc. of Neural Information Processing Systems (NIPS), Dec. 2016 (code,poster)

4. Arnaud Vandaele, Nicolas Gillis, Qi Lei, Kai Zhong, Inderjit Dhillon, “Efficient and Non-Convex Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization”, IEEE Transactions on Signal Processing 64.21 (2016): 5571-5584 (code)

3. Maria R. D'Orsogna, Qi Lei, Tom Chou, “First assembly times and equilibration in stochastic coagulation-fragmentation”, The Journal of Chemical Physics, 2015: 143.1, 014112

2. Jiazhou Chen, Qi Lei, Yongwei Miao, Qunsheng Peng, “Vectorization of Line Drawing Image based on Junction Analysis”, Science China Information Sciences, 2014:1-14 (code)

1. Jiazhou Chen, Qi Lei, Fan Zhong, Qunsheng Peng, “Interactive Tensor Field Design Based on Line Singularities”, Proceedings of the 13th International CAD/Graphics, 2013 (code)

Preprints

5. Tianci Liu, Quan Zhang, Qi Lei, “PANOM: Automatic Hyper-parameter Tuning for Inverse Problems”, NeurIPS 2021 Workshop on Deep Learning and Inverse Problems

4. Kaixuan Huang*, Sham M. Kakade*, Jason D. Lee*, Qi Lei*, “A Short Note on the Relationship of Information Gain and Eluder Dimension”, ICML 2021 Workshop on Reinforcement Learning Theory

3. Kurtland Chua, Qi Lei, Jason D Lee. “Provable Hierarchy-Based Meta-Reinforcement Learning”, arXiv preprint

2. Lemeng Wu, Mao Ye, Qi Lei, Jason D. Lee, and Qiang Liu. “Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting”, arXiv preprint

1. Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit Dhillon, Cho-Jui Hsieh. “CAT: Customized Adversarial Training for Improved Robustness”, arXiv preprint

Dissertation

“Provably Effective Algorithms for Min-Max Optimization” May, 2020 with Oden Institute Outstanding Dissertation Award

Patents

“Method and System for General and Efficient Time Series Representation Learning via Dynamic Time Warping”
with J. Yi, R. Vaculin, W. Sun

“Real-Time Cold Start Recommendation and Rationale within a Dialog System”
with J. Yi, R. Vaculin, M. Pietro