Publication List


43. Hoang Phan, Andrew G Wilson, Qi Lei. ‘‘Controllable Prompt Tuning For Balancing Group Distributional Robustness"To appear at ICML 2024

42. Hong Jun Jeon, Jason D Lee, Qi Lei, Benjamin Van Roy. ‘‘An Information-Theoretic Analysis of In-Context Learning", To appear at ICML 2024

41. Zhiyu Xue, Yinlong Dai, Qi Lei. ‘‘Exploring Minimally Sufficient Representation in Active Learning through Label-Irrelevant Patch Augmentation", CPAL 2024

40. Jianwei Li, Sheng Liu, Qi Lei. ‘‘Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning", FL@FM-NeurIPS 2023

39. Yijun Dong, Kevin Miller, Qi Lei, Rachel Ward. ‘‘Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering", NeurIPS 2023

38. Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee. ‘‘Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms", NeurIPS 2023

37. Jianwei Li, Qi Lei, Wei Cheng, Dongkuan Xu. ‘‘Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models", EMNLP-Main 2023

36. Jianwei Li, Weizhi Gao, Qi Lei, Dongkuan Xu. ‘‘Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection", EMNLP-Findings 2023

35. Tianci Liu, Tong Yang, Quan Zhang, Qi Lei. ‘‘Optimization for Amortized Inverse Problems", ICML 2023

34. Zihan Wang, Jason Lee, Qi Lei. ‘‘Reconstructing Training Data from Model Gradient, Provably", AISTATS 2023

33. Shuo Yang, Yijun Dong, Rachel Ward, Inderjit Dhillon, Sujay Sanghavi, Qi Lei. ‘‘Sample Efficiency of Data Augmentation Consistency Regularization", AISTATS 2023

32. Kurtland Chua, Qi Lei, Jason Lee. ‘‘Provable Hierarchy-Based Meta-Reinforcement Learning", AISTATS 2023

31. Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason Lee. ‘‘Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition", AISTATS 2023

30. Chun-Yin Huang, Qi Lei, Xiaoxiao Li, Efficient Medical Image Assessment via Self-supervised Learning, MICCAI Workshop, DALI 2022, with Best Paper Honorable Mention

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


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


“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