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06/10/2023
Any-dimensional equivariant neural networks
Traditional supervised learning aims to learn an unknown mapping by fitt...
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04/24/2023
Robust, randomized preconditioning for kernel ridge regression
This paper introduces two randomized preconditioning techniques for robu...
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07/09/2022
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
We analyze a stochastic approximation algorithm for decision-dependent p...
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10/04/2021
Clustering a Mixture of Gaussians with Unknown Covariance
We investigate a clustering problem with data from a mixture of Gaussian...
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06/17/2021
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization
Recent work has shown that stochastically perturbed gradient methods can...
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03/22/2020
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
This paper considers a canonical clustering problem where one receives u...
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04/22/2019
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
The task of recovering a low-rank matrix from its noisy linear measureme...
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01/06/2019
Composite optimization for robust blind deconvolution
The blind deconvolution problem seeks to recover a pair of vectors from ...
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05/04/2018