Articles avec mandats d'accès public - Qi LeiEn savoir plus
Disponibles quelque part : 27
Gradient coding: Avoiding stragglers in distributed learning
R Tandon, Q Lei, AG Dimakis, N Karampatziakis
International Conference on Machine Learning, 3368-3376, 2017
Exigences : US National Science Foundation, US Department of Defense
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
Exigences : US National Science Foundation, US Department of Defense
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
J Zhang, Q Lei, I Dhillon
International Conference on Machine Learning, 5806--5814, 2018
Exigences : US National Science Foundation
Inverting deep generative models, one layer at a time
Q Lei, A Jalal, IS Dhillon, AG Dimakis
Advances in neural information processing systems, 2019
Exigences : US National Science Foundation
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
Exigences : US National Science Foundation
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
Exigences : US National Science Foundation, Fonds de la Recherche Scientifique
A theory of label propagation for subpopulation shift
T Cai, R Gao, J Lee, Q Lei
International Conference on Machine Learning, 1170-1182, 2021
Exigences : US National Science Foundation, US Department of Defense
Coordinate-wise Power Method
Q Lei, K Zhong, IS Dhillon
Proceedings of the 30th International Conference on Neural Information …, 2016
Exigences : US National Science Foundation
How fine-tuning allows for effective meta-learning
K Chua, Q Lei, JD Lee
Advances in Neural Information Processing Systems 34, 2021
Exigences : US National Science Foundation, US Department of Defense
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
Exigences : US National Science Foundation
SGD Learns One-Layer Networks in WGANs
Q Lei, J Lee, A Dimakis, C Daskalakis
International Conference on Machine Learning, 2020
Exigences : US National Science Foundation, US Department of Energy, US Department of …
Near-optimal linear regression under distribution shift
Q Lei, W Hu, J Lee
International Conference on Machine Learning, 6164-6174, 2021
Exigences : US National Science Foundation, US Department of Defense
Compressed sensing with invertible generative models and dependent noise
J Whang, Q Lei, AG Dimakis
arXiv preprint arXiv:2003.08089, 2020
Exigences : US National Science Foundation
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
Exigences : National Natural Science Foundation of China
Solving Inverse Problems with a Flow-based Noise Model
J Whang, Q Lei, A Dimakis
International Conference on Machine Learning, 11146-11157, 2021
Exigences : US National Science Foundation
Fast convergence of langevin dynamics on manifold: Geodesics meet log-sobolev
X Wang, Q Lei, I Panageas
Advances in Neural Information Processing Systems 33, 18894-18904, 2020
Exigences : US National Science Foundation
Sample efficiency of data augmentation consistency regularization
S Yang, Y Dong, R Ward, IS Dhillon, S Sanghavi, Q Lei
International Conference on Artificial Intelligence and Statistics, 3825-3853, 2023
Exigences : US National Science Foundation, US Department of Defense
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
Exigences : US National Science Foundation, US Department of Defense, US National …
Reconstructing Training Data from Model Gradient, Provably
Z Wang, J Lee, Q Lei
International Conference on Artificial Intelligence and Statistics, 6595-6612, 2023
Exigences : US National Science Foundation, US Department of Defense
Primal-dual block generalized frank-wolfe
Q Lei, J Zhuo, C Caramanis, IS Dhillon, A Dimakis
Advances in Neural Information Processing Systems, 2019
Exigences : US National Science Foundation
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