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Perceptual adjustment queries and an inverted measurement paradigm for
  low-rank metric learning

Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning

8 September 2023
Austin Xu
Andrew D. McRae
Jingyan Wang
Mark A. Davenport
A. Pananjady
ArXivPDFHTML

Papers citing "Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning"

4 / 4 papers shown
Title
Optimal convex lifted sparse phase retrieval and PCA with an atomic
  matrix norm regularizer
Optimal convex lifted sparse phase retrieval and PCA with an atomic matrix norm regularizer
Andrew D. McRae
Justin Romberg
Mark A. Davenport
35
8
0
08 Nov 2021
Learning Low-Dimensional Metrics
Learning Low-Dimensional Metrics
Lalit P. Jain
Blake Mason
Robert D. Nowak
44
37
0
18 Sep 2017
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust
  Low-Rank Matrix Recovery
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery
Jianqing Fan
Weichen Wang
Ziwei Zhu
49
96
0
28 Mar 2016
Learning without Concentration
Learning without Concentration
S. Mendelson
90
333
0
01 Jan 2014
1