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DISCERN: Diversity-based Selection of Centroids for k-Estimation and
  Rapid Non-stochastic Clustering

DISCERN: Diversity-based Selection of Centroids for k-Estimation and Rapid Non-stochastic Clustering

14 October 2019
Ali Hassani
Amirarsalan Iranmanesh
M. Eftekhari
A. Salemi
ArXivPDFHTML

Papers citing "DISCERN: Diversity-based Selection of Centroids for k-Estimation and Rapid Non-stochastic Clustering"

4 / 4 papers shown
Title
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCL
SSL
171
4,051
0
17 Jun 2020
SCAN: Learning to Classify Images without Labels
SCAN: Learning to Classify Images without Labels
Wouter Van Gansbeke
Simon Vandenhende
Stamatios Georgoulis
Marc Proesmans
Luc Van Gool
VLM
SSL
87
535
0
25 May 2020
Unsupervised Pathology Image Segmentation Using Representation Learning
  with Spherical K-means
Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means
Takayasu Moriya
H. Roth
S. Nakamura
H. Oda
Kai Nagara
M. Oda
K. Mori
19
19
0
11 Apr 2018
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
281
13,079
0
12 Mar 2015
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