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Deep convolutional neural networks (CNNs) have demonstrated remarkable success in computer vision by supervisedly learning strong visual feature representations.
Exponentially weighted moving average control schemes: properties and enhancements
Lucas, J. M. and Saccucci, M. S · 1990
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Constrained k-means clustering with background knowledge
Wagstaff, K., Cardie, C., Rogers, S., Schrödl, S., et al · 2001
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Spectral learning
Kamvar, K., Sepandar, S., Klein, K., Dan, D., Manning, M., and Christopher, C · 2003
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Neighbourhood components analysis
Goldberger, J., Hinton, G. E., Roweis, S. T., and Salakhutdinov, R. R · 2005
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A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., and Teh, Y.-W · 2006
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Curriculum learning
Bengio, Y., Louradour, J., Collobert, R., and Weston, J · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A. and Hinton, G · 2009
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
Lee, H., Grosse, R., Ranganath, R., and Ng, A. Y · 2009
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., and Manzagol, P.-A · 2010
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Novel dataset for fine-grained image categorization
Khosla, A., Jayadevaprakash, N., Yao, B., and Fei-Fei, L · 2011
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Reading digits in natural images with unsupervised feature learning
Netzer, Y., Wang, T., Coates, A., Bissacco, A., Wu, B., and Ng, A. Y · 2011
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Sparse autoencoder
Ng, A · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
Wah, C., Branson, S., Welinder, P., Perona, P., and Belongie, S · 2011
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Robust boltzmann machines for recognition and denoising
Tang, Y., Salakhutdinov, R., and Hinton, G · 2012
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Data clustering: algorithms and applications
Aggarwal, C. C. and Reddy, C. K · 2013
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Constrained clustering: Effective constraint propagation with imperfect oracles
Zhu, X., Loy, C. C., and Gong, S · 2013
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Distilling the knowledge in a neural network
Hinton, G., Vinyals, O., and Dean, J · 2014
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Unsupervised visual representation learning by context prediction
Doersch, C., Gupta, A., and Efros, A. A · 2015
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Deep learning
LeCun, Y., Bengio, Y., and Hinton, G · 2015
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Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al · 2015
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Colorful image colorization
Zhang, R., Isola, P., and Efros, A. A · 2016
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Constrained clustering with imperfect oracles
Zhu, X., Loy, C. C., and Gong, S · 2016
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Unsupervised learning by predicting noise
Bojanowski, P. and Joulin, A · 2017
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Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization
Dizaji, K. G., Herandi, A., Deng, C., Cai, W., and Huang, H · 2017
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Multi-task curriculum transfer deep learning of clothing attributes
Dong, Q., Gong, S., and Zhu, X · 2017
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Representation learning by learning to count
Noroozi, M., Pirsiavash, H., and Favaro, P · 2017
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Unsupervised learning of visual representations using videos
Wang, X. and Gupta, A · 2015
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Adversarial feature learning
Donahue, J., Krähenbühl, P., and Darrell, T · 2016
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Deep learning
Goodfellow, I., Bengio, Y., and Courville, A · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Learning representations for automatic colorization
Larsson, G., Maire, M., and Shakhnarovich, G · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Noroozi, M. and Favaro, P · 2016
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D., et al · 2017
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Transitive invariance for self-supervised visual representation learning
Wang, X., He, K., and Gupta, A · 2017
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Towards k-means-friendly spaces: Simultaneous deep learning and clustering
Yang, B., Fu, X., Sidiropoulos, N. D., and Hong, M · 2017
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
Zhang, R., Isola, P., and Efros, A. A · 2017
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Deep clustering for unsupervised learning of visual features
Caron, M., Bojanowski, P., Joulin, A., and Douze, M · 2018
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Imbalanced deep learning by minority class incremental rectification
Dong, Q., Gong, S., and Zhu, X · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Wu, Z., Xiong, Y., Stella, X. Y., and Lin, D · 2018
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Single-label multi-class image classification by deep logistic regression
Dong, Q., Zhu, X., and Gong, S · 2019
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