Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming.
SIAM J. Optim., March, 2024
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality.
J. Mach. Learn. Res., 2024
Any-dimensional equivariant neural networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Optimal Convergence Rates for the Proximal Bundle Method.
SIAM J. Optim., 2023
Robust, randomized preconditioning for kernel ridge regression.
CoRR, 2023
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization.
SIAM J. Optim., September, 2022
Optimization of vaccination for COVID-19 in the midst of a pandemic.
Networks Heterog. Media, 2022
Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.
Found. Comput. Math., 2021
Clustering a Mixture of Gaussians with Unknown Covariance.
CoRR, 2021
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Efficient Clustering for Stretched Mixtures: Landscape and Optimality.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Local angles and dimension estimation from data on manifolds.
J. Multivar. Anal., 2019
Composite optimization for robust blind deconvolution.
CoRR, 2019
In Search of Balance: The Challenge of Generating Balanced Latin Rectangles.
Proceedings of the Integration of AI and OR Techniques in Constraint Programming, 2017