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This paper tackles the problem of learning a finer representation than the one provided by training labels.
WordNet: An Electronic Lexical Database
Christiane Fellbaum · 1998
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Neighbourhood components analysis
J. Goldberger, S. Roweis, Geoffrey E. Hinton, and R. Salakhutdinov · 2004
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Theory of classification: A survey of some recent advances
Stéphane Boucheron, Olivier Bousquet, and Gabor Lugosi · 2005
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Object retrieval with large vocabularies and fast spatial matching
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman · 2007
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Learning a nonlinear embedding by preserving class neighbourhood structure
R. Salakhutdinov and Geoffrey E. Hinton · 2007
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Automated flower classification over a large number of classes
M-E. Nilsback and A. Zisserman · 2008
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Deep supervised t-distributed embedding
Martin Renqiang Min, L. V. D. Maaten, Zineng Yuan, A. Bonner, and Z. Zhang · 2010
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From region similarity to category discovery
Carolina Galleguillos, Brian McFee, Serge J. Belongie, and Gert R. G. Lanckriet · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Hedging your bets: Optimizing accuracy-specificity trade-offs in large scale visual recognition
Jia Deng, J. Krause, A. Berg, and Li Fei-Fei · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Neural codes for image retrieval
Artem Babenko, Anton Slesarev, Alexander Chigorin, and Victor S. Lempitsky · 2014
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Food-101 – mining discriminative components with random forests
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool · 2014
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Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals
Minsu Cho, Suha Kwak, Cordelia Schmid, and Jean Ponce · 2015
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From categories to subcategories: Large-scale image classification with partial class label refinement
Marko Ristin, Juergen Gall, Matthieu Guillaumin, and Luc Van Gool · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Hyper-class augmented and regularized deep learning for fine-grained image classification
Saining Xie, Tianbao Yang, X. Wang, and Y. Lin · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deep image category discovery using a transferred similarity function
Yen-Chang Hsu, Zhaoyang Lv, and Zsolt Kira · 2016
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What makes imagenet good for transfer learning?
Mi-Young Huh, Pulkit Agrawal, and Alexei A. Efros · 2016
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Metric learning with adaptive density discrimination
Oren Rippel, Manohar Paluri, Piotr Dollár, and Lubomir D. Bourdev · 2016
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Yfcc100m: the new data in multimedia research
Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Lijia Li · 2016
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Unsupervised learning by predicting noise
Piotr Bojanowski and Armand Joulin · 2017
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Accurate, large minibatch sgd: Training imagenet in 1 hour
Priya Goyal, Piotr Dollár, Ross B. Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Cnn-rnn: a large-scale hierarchical image classification framework
Yanming Guo, Yu Liu, Erwin M. Bakker, Yuanhao Guo, and Michael S. Lew · 2017
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The inaturalist challenge 2017 dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Alexander Shepard, Hartwig Adam, Pietro Perona, and Serge J. Belongie · 2017
Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, and Herve Jegou · 2019
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Unsupervised image matching and object discovery as optimization
Huy V. Vo, Francis Bach, Minsu Cho, Kai Han, Yann LeCun, Patrick Pérez, and Jean Ponce · 2019
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A hierarchical loss and its problems when classifying non-hierarchically
Cinna Wu, M. Tygert, and Y. LeCun · 2019
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Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, and Quoc V. Le · 2019
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Self-training with noisy student improves imagenet classification
Qizhe Xie, Eduard H. Hovy, Minh-Thang Luong, and Quoc V. Le · 2019
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No fuss distance metric learning using proxies
Yair Movshovitz-Attias, A. Toshev, T. Leung, S. Ioffe, and S. Singh · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross B. Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Diana-Terry Hibbitts :
Authors:copyright for Figure 1 images from inaturalist-2018, top to down, left to right, employed for illustration of research work · 2018
Cited alongside, same era.
Large scale fine-grained categorization and domain-specific transfer learning
Yin Cui, Yang Song, Chen Sun, Andrew Howard, and Serge J. Belongie · 2018
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Bag of tricks for image classification with convolutional neural networks
Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, and Mu Li · 2018
Cited alongside, same era.
The inaturalist challenge 2018 dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Alexander Shepard, Hartwig Adam, Pietro Perona, and Serge J. Belongie · 2018
Cited alongside, same era.
Improving generalization via scalable neighborhood component analysis
Zhirong Wu, Alexei A Efros, and Stella Yu · 2018
Cited alongside, same era.
Ismet Zeki Yalniz, Hervé Jégou, Kan Chen, Manohar Paluri, and Dhruv Kumar Mahajan · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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S4l: Self-supervised semi-supervised learning
Xiaohua Zhai, A. Oliver, A. Kolesnikov, and Lucas Beyer · 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 E. Hinton · 2020
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Feature space augmentation for long-tailed data
P. Chu, Xiao Bian, Shaopeng Liu, and Haibin Ling · 2020
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Underspecification presents challenges for credibility in modern machine learning, 2020
Alexander D’Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, and D. Sculley · 2020
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Learning representations by predicting bags of visual words
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, and Michal Valko · 2020
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The open images dataset v4
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper R. R. Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Tom Duerig, and Vittorio Ferrari · 2020
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Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross B. Girshick, Kaiming He, and Piotr Dollár · 2020
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Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Kihyuk Sohn, David Berthelot, C. Li, Zizhao Zhang, N. Carlini, E. D. Cubuk, Alex Kurakin, Han Zhang, and Colin Raffel · 2020
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Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis
Eu Wern Teh, Terrance Devries, and Graham W. Taylor · 2020
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Fixing the train-test resolution discrepancy: Fixefficientnet
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, and Hervé Jégou · 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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Toward unsupervised, multi-object discovery in large-scale image collections
Huy V. Vo, Patrick Pérez, and Jean Ponce · 2020
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Clusterfit: Improving generalization of visual representations
Xueting Yan, Ishan Misra, Abhinav Gupta, Deepti Ghadiyaram, and Dhruv Kumar Mahajan · 2020
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Random erasing data augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang · 2020
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