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Convolutional networks have marked their place over the last few years as the best performing model for various visual tasks.
Signature verification using a “siamese” time delay neural network
Jane Bromley, James W Bentz, Léon Bottou, Isabelle Guyon, Yann LeCun, Cliff Moore, Eduard Säckinger, and Roopak Shah · 1993
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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To recognize shapes, first learn to generate images
Geoffrey E Hinton · 2007
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
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What is the best multi-stage architecture for object recognition?
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio Ranzato, and Yann LeCun · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen · 2010
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Deconvolutional networks
Matthew D Zeiler, Dilip Krishnan, Graham W Taylor, and Rob Fergus · 2010
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An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Andrew Y Ng, and Honglak Lee · 2011
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Sparse autoencoder
Andrew Ng · 2011
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Learning feature representations with k-means
Adam Coates and Andrew Y Ng · 2012
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ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Cited alongside, same era.
Direct modeling of complex invariances for visual object features
Ka Y Hui · 2013
Cited alongside, same era.
Min Lin, Qiang Chen, and Shuicheng Yan · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Cited alongside, same era.
Learning word embeddings efficiently with noise-contrastive estimation
Andriy Mnih and Koray Kavukcuoglu · 2013
Cited alongside, same era.
Regularization of neural networks using dropconnect
Li Wan, Matthew Zeiler, Sixin Zhang, Yann L Cun, and Rob Fergus · 2013
Deep metric learning using triplet network
Elad Hoffer and Nir Ailon · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Learning to segment object candidates
Pedro O Pinheiro, Ronan Collobert, and Piotr Dollar · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Semi-supervised learning with ladder networks
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Cited alongside, same era.
Discriminative unsupervised feature learning with convolutional neural networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
Cited alongside, same era.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
An analysis of unsupervised pre-training in light of recent advances
Tom Le Paine, Pooya Khorrami, Wei Han, and Thomas S Huang · 2014
Cited alongside, same era.
Cnn features off-the-shelf: an astounding baseline for recognition
Ali Razavian, Hossein Azizpour, Josephine Sullivan, and Stefan Carlsson · 2014
Cited alongside, same era.
Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, and Tapani Raiko · 2015
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Deep representation learning with target coding
Shuo Yang, Ping Luo, Chen Change Loy, Kenneth W Shum, and Xiaoou Tang · 2015
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Stacked what-where auto-encoders
Junbo Zhao, Michael Mathieu, Ross Goroshin, and Yann Lecun · 2015
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Pn-net: Conjoined triple deep network for learning local image descriptors
Vassileios Balntas, Edward Johns, Lilian Tang, and Krystian Mikolajczyk · 2016
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