ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1802.00381
  4. Cited By
Signal-plus-noise matrix models: eigenvector deviations and fluctuations

Signal-plus-noise matrix models: eigenvector deviations and fluctuations

1 February 2018
Joshua Cape
M. Tang
Carey E. Priebe
ArXivPDFHTML

Papers citing "Signal-plus-noise matrix models: eigenvector deviations and fluctuations"

8 / 8 papers shown
Title
Elliptic PDE learning is provably data-efficient
Elliptic PDE learning is provably data-efficient
N. Boullé
Diana Halikias
Alex Townsend
20
18
0
24 Feb 2023
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Dapeng Yao
Fangzheng Xie
Yanxun Xu
31
1
0
21 Jul 2022
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
Joshua Agterberg
Jeremias Sulam
21
0
0
08 Feb 2022
The multilayer random dot product graph
The multilayer random dot product graph
Andrew Jones
Patrick Rubin-Delanchy
6
35
0
20 Jul 2020
Manifold structure in graph embeddings
Manifold structure in graph embeddings
Patrick Rubin-Delanchy
19
24
0
09 Jun 2020
On Two Distinct Sources of Nonidentifiability in Latent Position Random
  Graph Models
On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models
Joshua Agterberg
M. Tang
Carey E. Priebe
CML
30
9
0
31 Mar 2020
Efficient Estimation for Random Dot Product Graphs via a One-step
  Procedure
Efficient Estimation for Random Dot Product Graphs via a One-step Procedure
Fangzheng Xie
Yanxun Xu
27
21
0
10 Oct 2019
Estimating Mixed Memberships with Sharp Eigenvector Deviations
Estimating Mixed Memberships with Sharp Eigenvector Deviations
Xueyu Mao
Purnamrita Sarkar
Deepayan Chakrabarti
14
84
0
01 Sep 2017
1