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The availability of large labeled datasets has allowed Convolutional Network models to achieve impressive recognition results.
Backpropagation applied to handwritten zip code recognition
LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., and Jackel, L. D · 1989
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Discovering informative patterns and data cleaning
Guyon, Isabelle, Matic, Nada, and Vapnik, Vladimir · 1996
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Design of robust neural network classifiers
Larsen, J., Nonboe, L., Hintz-Madsen, M., and Hansen, L.K · 1998
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Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998
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Identifying mislabeled training data
Brodley, Carla E. and Friedl, Mark A · 1999
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Decontamination of training samples for supervised pattern recognition methods
Barandela, Ricardo and Gasca, Eduardo · 2000
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Randomized response, statistical disclosure control and misclassificatio: a review
van den Hout, Ardo and van der Heijden, Peter G.M · 2002
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Semi-supervised learning using gaussian fields and harmonic functions
Zhu, X., Ghahramani, Z., and Laffery, J · 2003
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Learning with local and global consistency
Zhou, D., Bousquet, O., Lal, T., Weston, J., and Scholkopf, B · 2004
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Class noise vs. attribute noise: A quantitative study
Zhu, Xingquan and Wu, Xindong · 2004
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Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Zhu, X. and Lafferty, J · 2005
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Reducing the dimensionality of data with neural networks
Hinton, G. E. and Salakhutdinov, R. R · 2006
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Class noise and supervised learning in medical domains: The effect of feature extraction
Pechenizkiy, M., Tsymbal, A., Puuronen, S., and Pechenizkiy, O · 2006
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Large-scale manifold learning
Talwalkar, A., Kumar, S., and Rowley, H · 2008
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80 million tiny images: A large data set for nonparametric object and scene recognition
Torralba, A., Fergus, R., and Freeman, W.T · 2008
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Semi-supervised learning literature survey
Zhu, Xiaojin · 2008
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Imagenet: A large-scale hierarchical image database
Deng, Jia, Dong, Wei, Socher, R., Li, Li-Jia, Li, Kai, and Fei-Fei, Li · 2009
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Semi-supervised learning in gigantic image collections
Fergus, Rob, Weiss, Yair, and Torralba, Antonio · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, Alex and Hinton, Geoffrey · 2009
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Reading digits in natural images with unsupervised feature learning
Netzer, Yuval, Wang, Tao, Coates, Adam, Bissacco, Alessandro, Wu, Bo, and Ng, Andrew Y · 2011
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Label-noise robust logistic regression and its applications
Bootkrajang, Jakramate and Kabán, Ata · 2012
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cuda-convnet
Krizhevsky, Alex · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E · 2012
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Learning to label aerial images from noisy data
Mnih, Volodymyr and Hinton, Geoffrey · 2012
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Building high-level features using large scale unsupervised learning
Le, Q.V · 2013
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
Lee, Honglak, Grosse, Roger, Ranganath, Rajesh, and Ng, Andrew Y · 2009
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Understanding and evaluating blind deconvolution algorithms
Levin, A., Weiss, Y., Durand, F., and Freeman, W. T · 2009
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Why does unsupervised pre-training help deep learning?
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, Manzagol, Pierre-Antoine, Vincent, Pascal, and Bengio, Samy · 2010
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Quality management on amazon mechanical turk
Ipeirotis, Panagiotis G., Provost, Foster, and Wang, Jing · 2010
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A study of the effect of different types of noise on the precision of supervised learning techniques
Nettleton, David, Orriols-Puig, Albert, and Fornells, Albert · 2010
Cited alongside, same era.
Torch7: A matlab-like environment for machine learning
Collobert, Ronan, Kavukcuoglu, Koray, and Farabet, Clément · 2011
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Learning with noisy labels
Natarajan, Nagarajan, Dhillon, Inderjit, Ravikumar, Pradeep, and Tewari, Ambuj · 2013
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Classification in the presence of label noise: A survey
Frenay, B. and Verleysen, M · 2014
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Caffe: Convolutional architecture for fast feature embedding
Jia, Yangqing, Shelhamer, Evan, Donahue, Jeff, Karayev, Sergey, Long, Jonathan, Girshick, Ross, Guadarrama, Sergio, and Darrell, Trevor · 2014
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Sermanet, Pierre, Eigen, David, Zhang, Xiang, Mathieu, Michael, Fergus, Rob, and LeCun, Yann · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, Karen and Zisserman, Andrew · 2014
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DeepFace: Closing the Gap to Human-Level Performance in Face Verification
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