Christian Kümmerle | DeepAI

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∙ 06/08/2023

Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares

We propose a new algorithm for the problem of recovering data that adher...

0 Christian Kümmerle, et al. ∙

∙ 12/01/2022

Learning Transition Operators From Sparse Space-Time Samples

We consider the nonlinear inverse problem of learning a transition opera...

0 Christian Kümmerle, et al. ∙

∙ 06/03/2021

A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples

We propose an iterative algorithm for low-rank matrix completion that ca...

0 Christian Kümmerle, et al. ∙

∙ 01/20/2021

Dictionary-Sparse Recovery From Heavy-Tailed Measurements

The recovery of signals that are sparse not in a basis, but rather spars...

0 Pedro Abdalla, et al. ∙

∙ 12/22/2020

Iteratively Reweighted Least Squares for ℓ_1-minimization with Global Linear Convergence Rate

Iteratively Reweighted Least Squares (IRLS), whose history goes back mor...

0 Christian Kümmerle, et al. ∙

∙ 10/23/2020

On the robustness of noise-blind low-rank recovery from rank-one measurements

We prove new results about the robustness of well-known convex noise-bli...

0 Felix Krahmer, et al. ∙

∙ 09/07/2020

Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method

We propose an iterative algorithm for low-rank matrix completion that ca...

0 Christian Kümmerle, et al. ∙

∙ 07/16/2019

On the geometry of polytopes generated by heavy-tailed random vectors

We study the geometry of centrally-symmetric random polytopes, generated...

0 Olivier Guédon, et al. ∙

∙ 01/17/2019

The Oracle of DLphi

We present a novel technique based on deep learning and set theory which...

0 Weston Baines, et al. ∙

∙ 11/19/2018

Denoising and Completion of Structured Low-Rank Matrices via Iteratively Reweighted Least Squares

We propose a new Iteratively Reweighted Least Squares (IRLS) algorithm f...

0 Christian Kümmerle, et al. ∙

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