research
∙
10/31/2020
Optimal Sample Complexity of Gradient Descent for Amplitude Flow via Non-Lipschitz Matrix Concentration
We consider the problem of recovering a real-valued n-dimensional signal...
share
research
∙
08/24/2020
Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors
Advances in compressive sensing provided reconstruction algorithms of sp...
research
∙
06/14/2020
Nonasymptotic Guarantees for Low-Rank Matrix Recovery with Generative Priors
Many problems in statistics and machine learning require the reconstruct...
research
∙
07/11/2018
Phase Retrieval Under a Generative Prior
The phase retrieval problem asks to recover a natural signal y_0 ∈R^n fr...
research
∙
05/22/2018
Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior
Deep neural networks provide state-of-the-art performance for image deno...
research
∙
01/30/2017
A Survey of Structure from Motion
The structure from motion (SfM) problem in computer vision is the proble...
research
∙
08/07/2016
ShapeFit and ShapeKick for Robust, Scalable Structure from Motion
We introduce a new method for location recovery from pair-wise direction...
research
∙
06/04/2015
