ArticleMathematical programming2019
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval.
Article in Mathematical programming, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning.Proceedings of machine learning research · 2026Article
- Pneumatically-Actuated Liquid Metal-Based Frequency Reconfigurable Antenna.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Review
- Wasserstein F-tests for Fréchet regression on Bures-Wasserstein manifolds.Journal of machine learning research : JMLR · 2025Article
- SPRING, an effective and reliable framework for image reconstruction in single-particle Coherent Diffraction Imaging.npj computational materials · 2025Article
- Non-convex optimization for inverse problem solving in computer-generated holography.Light, science & applications · 2024Review
- Approximate message passing from random initialization with applications toProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs.Journal of the American Statistical Association · 2023Article
- Image Classification of Wheat Rust Based on Ensemble Learning.Sensors (Basel, Switzerland) · 2022Article
- BRIDGING CONVEX AND NONCONVEX OPTIMIZATION IN ROBUST PCA: NOISE, OUTLIERS, AND MISSING DATA.Annals of statistics · 2021Article
- A selective overview of deep learning.Statistical science : a review journal of the Institute of Mathematical Statistics · 2021Article
- Recognition of industrial machine parts based on transfer learning with convolutional neural network.PloS one · 2021Article
- NOISY MATRIX COMPLETION: UNDERSTANDING STATISTICAL GUARANTEES FOR CONVEX RELAXATION VIA NONCONVEX OPTIMIZATION.SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics · 2020Article
- SPECTRAL METHOD AND REGULARIZED MLE ARE BOTH OPTIMAL FOR TOP-Annals of statistics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This paper considers the problem of solving systems of quadratic equations, namely, recovering an object of interest
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.