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We propose a novel framework for image clustering that incorporates joint representation learning and clustering.
Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Imagenet: A large-scale hierarchical image database
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Learning multiple layers of features from tiny images
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Discriminative unsupervised feature learning with convolutional neural networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2016
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SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Unsupervised deep embedding for clustering analysis
Junyuan Xie, Ross Girshick, and Ali Farhadi · 2016
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Joint unsupervised learning of deep representations and image clusters
Jianwei Yang, Devi Parikh, and Dhruv Batra · 2016
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Deep adaptive image clustering
Jianlong Chang, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2017
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Nonparametric variational auto-encoders for hierarchical representation learning
Prasoon Goyal, Zhiting Hu, Xiaodan Liang, Chenyu Wang, Eric P Xing, and Carnegie Mellon · 2017
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Variational deep embedding: An unsupervised and generative approach to clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan, Bangsheng Tang, and Hanning Zhou · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Towards k-means-friendly spaces: Simultaneous deep learning and clustering
Bo Yang, Xiao Fu, Nicholas D Sidiropoulos, and Mingyi Hong · 2017
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Deep clustering by gaussian mixture variational autoencoders with graph embedding
Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang · 2019
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Unsupervised embedding learning via invariant and spreading instance feature
Mang Ye, Xu Zhang, Pong C Yuen, and Shih-Fu Chang · 2019
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Local aggregation for unsupervised learning of visual embeddings
Chengxu Zhuang, Alex Lin Zhai, and Daniel Yamins · 2019
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
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Self-labelling via simultaneous clustering and representation learning
Yuki Markus Asano, Christian Rupprecht, and Andrea Vedaldi · 2019
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Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring
David Berthelot, Nicholas Carlini, Ekin D Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, and Colin Raffel · 2019
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Mixmatch: A holistic approach to semi-supervised learning
David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, and Colin A Raffel · 2019
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Deep discriminative clustering analysis
Jianlong Chang, Yiwen Guo, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2019
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Randaugment: Practical data augmentation with no separate search
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2019
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Deep semantic clustering by partition confidence maximisation
Jiabo Huang, Shaogang Gong, and Xiatian Zhu · 2020
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, Richard Socher, and Steven CH Hoi · 2020
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Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou, and Xi Peng · 2020
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Formal limitations on the measurement of mutual information
David McAllester and Karl Stratos · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Improving unsupervised image clustering with robust learning
Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, and Meeyoung Cha · 2020
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Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D Cubuk, Alex Kurakin, Han Zhang, and Colin Raffel · 2020
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Scan: Learning to classify images without labels
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, and Luc Van Gool · 2020
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Delving into inter-image invariance for unsupervised visual representations
Jiahao Xie, Xiaohang Zhan, Ziwei Liu, Yew Soon Ong, and Chen Change Loy · 2020
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Learning diverse and discriminative representations via the principle of maximal coding rate reduction
Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, and Yi Ma · 2020
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Online deep clustering for unsupervised representation learning
Xiaohang Zhan, Jiahao Xie, Ziwei Liu, Yew-Soon Ong, and Chen Change Loy · 2020
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Deep robust clustering by contrastive learning
Huasong Zhong, Chong Chen, Zhongming Jin, and Xian-Sheng Hua · 2020
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