Gradient coding: Avoiding stragglers in distributed learning R Tandon, Q Lei, AG Dimakis, N Karampatziakis International Conference on Machine Learning, 3368-3376, 2017 | 519 | 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 | 258 | 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 | 178 | 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 | 159 | 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 | 122 | 2018 |
Cat: Customized adversarial training for improved robustness M Cheng, Q Lei, PY Chen, I Dhillon, CJ Hsieh IJCAI, 673-679, 2022 | 108 | 2022 |
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 |
Gradient coding R Tandon, Q Lei, AG Dimakis, N Karampatziakis arXiv preprint arXiv:1612.03301, 2016 | 100 | 2016 |
Similarity Preserving Representation Learning for Time Series Clustering. Q Lei, J Yi, R Vaculin, L Wu, IS Dhillon IJCAI 19, 2845-2851, 2019 | 96 | 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 | 60 | 2019 |
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 |
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 | 59 | 2017 |
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 | 53 | 2016 |
Coordinate-wise Power Method Q Lei, K Zhong, IS Dhillon Proceedings of the 30th International Conference on Neural Information …, 2016 | 51 | 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 | 48 | 2021 |
How fine-tuning allows for effective meta-learning K Chua, Q Lei, JD Lee Advances in Neural Information Processing Systems 34, 2021 | 47 | 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 | 47 | 2021 |
SGD Learns One-Layer Networks in WGANs Q Lei, J Lee, A Dimakis, C Daskalakis International Conference on Machine Learning, 2020 | 43 | 2020 |
Near-optimal linear regression under distribution shift Q Lei, W Hu, J Lee International Conference on Machine Learning, 6164-6174, 2021 | 40 | 2021 |
Compressed sensing with invertible generative models and dependent noise J Whang, Q Lei, AG Dimakis arXiv preprint arXiv:2003.08089, 2020 | 35 | 2020 |