Qi Lei
Qi Lei
Associate Research Scholar at ECE Department, Princeton University
Verified email at princeton.edu - Homepage
Title
Cited by
Cited by
Year
Gradient coding: Avoiding stragglers in distributed learning
R Tandon, Q Lei, AG Dimakis, N Karampatziakis
International Conference on Machine Learning, 3368-3376, 2017
382*2017
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
892018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
J Zhang, Q Lei, I Dhillon
International Conference on Machine Learning, 5806--5814, 2018
802018
Few-shot learning via learning the representation, provably
SS Du, W Hu, SM Kakade, JD Lee, Q Lei
International Conference on Learning Representations, 2021
772021
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
55*2019
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
47*2016
Coordinate-wise Power Method
Q Lei, K Zhong, IS Dhillon
Proceedings of the 30th International Conference on Neural Information …, 2016
442016
Predicting what you already know helps: Provable self-supervised learning
JD Lee, Q Lei, N Saunshi, J Zhuo
arXiv preprint arXiv:2008.01064, 2020
402020
A greedy approach for budgeted maximum inner product search
HF Yu, CJ Hsieh, Q Lei, IS Dhillon
arXiv preprint arXiv:1610.03317, 2016
352016
Cat: Customized adversarial training for improved robustness
M Cheng, Q Lei, PY Chen, I Dhillon, CJ Hsieh
arXiv preprint arXiv:2002.06789, 2020
342020
Inverting deep generative models, one layer at a time
Q Lei, A Jalal, IS Dhillon, AG Dimakis
Advances in neural information processing systems, 2019
342019
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
302018
Similarity Preserving Representation Learning for Time Series Analysis
Q Lei, J Yi, R Vaculin, L Wu, IS Dhillon
arXiv preprint arXiv:1702.03584, 2017
26*2017
SGD Learns One-Layer Networks in WGANs
Q Lei, J Lee, A Dimakis, C Daskalakis
International Conference on Machine Learning, 2020
222020
Similarity Preserving Representation Learning for Time Series Clustering.
Q Lei, J Yi, R Vaculin, L Wu, IS Dhillon
IJCAI 19, 2845-2851, 2019
212019
Doubly greedy primal-dual coordinate descent for sparse empirical risk minimization
Q Lei, IEH Yen, C Wu, IS Dhillon, P Ravikumar
International Conference on Machine Learning, 2034-2042, 2017
172017
Vectorization of line drawing image based on junction analysis
JZ Chen, Q Lei, YW Miao, QS Peng
Science China Information Sciences 58 (7), 1-14, 2015
172015
Solving Inverse Problems with a Flow-based Noise Model
J Whang, Q Lei, A Dimakis
International Conference on Machine Learning, 11146-11157, 2021
16*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
152021
Primal-dual block generalized frank-wolfe
Q Lei, J Zhuo, C Caramanis, IS Dhillon, A Dimakis
Advances in Neural Information Processing Systems, 2019
112019
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Articles 1–20