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Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural
  Networks
v1v2v3 (latest)

Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks

18 August 2015
A. Jansen
Gregory Sell
V. Lyzinski
ArXiv (abs)PDFHTML

Papers citing "Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks"

4 / 4 papers shown
Title
Deep Diffusion Maps
Deep Diffusion Maps
Sergio García-Heredia
Ángela Fernández
Carlos M. Alaíz
39
0
0
09 May 2025
Limit theorems for out-of-sample extensions of the adjacency and
  Laplacian spectral embeddings
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith D. Levin
Fred Roosta
M. Tang
Michael W. Mahoney
Carey E. Priebe
47
6
0
29 Sep 2019
Billion-scale semi-supervised learning for image classification
Billion-scale semi-supervised learning for image classification
I. Z. Yalniz
Hervé Jégou
Kan Chen
Manohar Paluri
D. Mahajan
SSL
143
464
0
02 May 2019
Low-shot learning with large-scale diffusion
Low-shot learning with large-scale diffusion
Matthijs Douze
Arthur Szlam
Bharath Hariharan
Hervé Jégou
85
113
0
07 Jun 2017
1