Qi Lei

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Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerified email at princeton.edu
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonVerified email at cs.utexas.edu
Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Jinfeng Yi (易津锋)Verified email at jd.com
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Pin-Yu ChenPrincipal Research Scientist, IBM Research AI; MIT-IBM Watson AI Lab; RPI-IBM AIRCVerified email at ibm.com
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Kai ZhongApplied Scientist, AmazonVerified email at amazon.com
Ian En-Hsu YenPhD, Machine Learning Department, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Amir GholamiResearch Scientist, University of California, BerkeleyVerified email at eecs.berkeley.edu
Kurt KeutzerProfessor of the Graduate School, EECS, University of California, BerkeleyVerified email at berkeley.edu
Michael MahoneyProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Jiong ZhangSenior Applied Scientist, AmazonVerified email at utexas.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinVerified email at utexas.edu
Hsiang-Fu YuPrincipal Applied Scientist at AmazonVerified email at cs.utexas.edu
Arnaud VandaeleMathematics and Operational Research, Faculté Polytechnique, Université de Mons, BelgiumVerified email at umons.ac.be
Nicolas GillisUniversity of MonsVerified email at umons.ac.be
Rachel WardVerified email at math.utexas.edu
Constantinos DaskalakisProfessor of Computer Science, MITVerified email at csail.mit.edu

Qi Lei

Assistant Professor of Mathematics and Data Science, New York University

Verified email at nyu.edu - Homepage

Machine Learning Optimization Deep Learning


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Gradient coding: Avoiding stragglers in distributed learning R Tandon, Q Lei, AG Dimakis, N Karampatziakis International Conference on Machine Learning, 3368-3376, 2017	546	2017
Few-shot learning via learning the representation, provably SS Du, W Hu, SM Kakade, JD Lee, Q Lei International Conference on Learning Representations, 2021	270	2021
Predicting what you already know helps: Provable self-supervised learning JD Lee, Q Lei, N Saunshi, J Zhuo Advances in Neural Information Processing Systems 34, 2021	185	2021
Hessian-based analysis of large batch training and robustness to adversaries Z Yao, A Gholami, Q Lei, K Keutzer, MW Mahoney Advances in Neural Information Processing Systems 31, 4949-4959, 2018	171	2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization J Zhang, Q Lei, I Dhillon International Conference on Machine Learning, 5806--5814, 2018	129	2018
Cat: Customized adversarial training for improved robustness M Cheng, Q Lei, PY Chen, I Dhillon, CJ Hsieh IJCAI, 673-679, 2022	119	2022
Gradient coding R Tandon, Q Lei, AG Dimakis, N Karampatziakis arXiv preprint arXiv:1612.03301, 2016	102	2016
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Q Lei, L Wu, PY Chen, A Dimakis, IS Dhillon, MJ Witbrock Systems and Machine Learning (SysML), 2019	100	2019
Similarity Preserving Representation Learning for Time Series Clustering. Q Lei, J Yi, R Vaculin, L Wu, IS Dhillon IJCAI 19, 2845-2851, 2019	99	2019
Inverting deep generative models, one layer at a time Q Lei, A Jalal, IS Dhillon, AG Dimakis Advances in neural information processing systems, 2019	61	2019
A greedy approach for budgeted maximum inner product search HF Yu, CJ Hsieh, Q Lei, IS Dhillon Advances in neural information processing systems 30, 2017	61	2017
Random Warping Series: A Random Features Method for Time-Series Embedding L Wu, IEH Yen, J Yi, F Xu, Q Lei, M Witbrock In International Conference on Artificial Intelligence and Statistics, 793-802, 2018	60	2018
Efficient and non-convex coordinate descent for symmetric nonnegative matrix factorization A Vandaele, N Gillis, Q Lei, K Zhong, I Dhillon IEEE Transactions on Signal Processing 64 (21), 5571-5584, 2016	57	2016
Coordinate-wise Power Method Q Lei, K Zhong, IS Dhillon Proceedings of the 30th International Conference on Neural Information …, 2016	53	2016
A theory of label propagation for subpopulation shift T Cai, R Gao, J Lee, Q Lei International Conference on Machine Learning, 1170-1182, 2021	51	2021
How fine-tuning allows for effective meta-learning K Chua, Q Lei, JD Lee Advances in Neural Information Processing Systems 34, 2021	49	2021
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes Q Lei, SG Nagarajan, I Panageas, X Wang International Conference on Artificial Intelligence and Statistics, 2021	49	2021
SGD Learns One-Layer Networks in WGANs Q Lei, J Lee, A Dimakis, C Daskalakis International Conference on Machine Learning, 2020	44	2020
Near-optimal linear regression under distribution shift Q Lei, W Hu, J Lee International Conference on Machine Learning, 6164-6174, 2021	41	2021
Compressed sensing with invertible generative models and dependent noise J Whang, Q Lei, AG Dimakis arXiv preprint arXiv:2003.08089, 2020	36	2020

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