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We study in this paper the problem of jointly clustering and learning representations.
The Hungarian Method for the Assignment Problem
H. W. Kuhn · 1955
Earlier work this paper cites.
Some Methods for Classification and Analysis of Multivariate Observations
J. MacQueen · 1967
Earlier work this paper cites.
FCM: The Fuzzy c-Means Clustering Algorithm
J. C. Bezdek, R. Ehrlich, and W. Full · 1984
Earlier work this paper cites.
A Deterministic Annealing Approach to Clustering
K. Rose, E. Gurewitz, and G. Fox · 1990
Earlier work this paper cites.
Greedy Layer-Wise Training of Deep Networks
Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle · 2006
Earlier work this paper cites.
Pattern Recognition and Machine Learning
C. M. Bishop · 2006
Earlier work this paper cites.
Reducing the Dimensionality of Data with Neural Networks
G. E. Hinton and R. R. Salakhutdinov · 2006
Earlier work this paper cites.
K-Means++: The Advantages of Careful Seeding
D. Arthur and S. Vassilvitskii · 2007
Earlier work this paper cites.
Visualizing Data using t-SNE
L. van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Understanding the Difficulty of Training Deep Feedforward Neural Networks
X. Glorot and Y. Bengio · 2010
Earlier work this paper cites.
Rectified Linear Units Improve Restricted Boltzmann Machines
V. Nair and G. E. Hinton · 2010
Earlier work this paper cites.
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
N. X. Vinh, J. Epps, and J. Bailey · 2010
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Later among the works it cites.
Deep Subspace Clustering Networks
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Later among the works it cites.
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
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The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
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Clustering with Deep Learning: Taxonomy and New Methods
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CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data
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