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This paper introduces Ranking Info Noise Contrastive Estimation (RINCE), a new member in the family of InfoNCE losses that preserves a ranked ordering of positive samples.
Roberta: A robustly optimized bert pretraining approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; and Stoyanov, V. 2019 · 1907
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Improved baselines with momentum contrastive learning
Chen, X.; Fan, H.; Girshick, R.; and He, K. 2020b · 2003
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Learning to Rank Using Gradient Descent
Burges, C.; Shaked, T.; Renshaw, E.; Lazier, A.; Deeds, M.; Hamilton, N.; and Hullender, G. 2005 · 2005
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What makes for good views for contrastive learning
Tian, Y.; Sun, C.; Poole, B.; Krishnan, D.; Schmid, C.; and Isola, P. 2020 · 2005
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Distance Metric Learning for Large Margin Nearest Neighbor Classification
Weinberger, K. Q.; Blitzer, J.; and Saul, L. 2006 · 2006
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Learning to rank: from pairwise approach to listwise approach
Cao, Z.; Qin, T.; Liu, T.-Y.; Tsai, M.-F.; and Li, H. 2007 · 2007
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Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks
Lee, D.; and Cheon, Y. 2020 · 2007
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Contrastive training for improved out-of-distribution detection
Winkens, J.; Bunel, R.; Roy, A. G.; Stanforth, R.; Natarajan, V.; Ledsam, J. R.; MacWilliams, P.; Kohli, P.; Karthikesalingam, A.; Kohl, S.; et al. 2020 · 2007
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Visualizing data using t-SNE
Van der Maaten, L.; and Hinton, G. 2008 · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A.; Hinton, G.; et al. 2009 · 2009
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Learning to Rank for Information Retrieval
Liu, T.-Y. 2009 · 2009
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Visual and semantic similarity in imagenet
Deselaers, T.; and Ferrari, V. 2011 · 2011
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Boosting Contrastive Self-Supervised Learning with False Negative Cancellation
Huynh, T.; Kornblith, S.; Walter, M. R.; Maire, M.; and Khademi, M. 2020 · 2011
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HMDB: A large video database for human motion recognition
Kuehne, H.; Jhuang, H.; Garrote, E.; Poggio, T.; and Serre, T. 2011 · 2011
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Scikit-learn: Machine Learning in Python
Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; Vanderplas, J.; Passos, A.; Cournapeau, D.; Brucher, M.; Perrot, M.; and Duchesnay, E. 2011 · 2011
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UCF101: A dataset of 101 human actions classes from videos in the wild
Soomro, K.; Zamir, A. R.; and Shah, M. 2012 · 2012
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One weird trick for parallelizing convolutional neural networks
Krizhevsky, A. 2014 · 2014
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Adam: A method for stochastic optimization
Kingma, D.; and Ba, J. 2015 · 2015
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Tiny imagenet visual recognition challenge
Le, Y.; and Yang, X. 2015 · 2015
Cited alongside, same era.
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
Dosovitskiy, A.; Fischer, P.; Springenberg, J. T.; Riedmiller, M.; and Brox, T. 2016 · 2016
Cited alongside, same era.
Improved Deep Metric Learning with Multi-class N-pair Loss Objective
Sohn, K. 2016 · 2016
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; and Wojna, Z. 2016 · 2016
Cited alongside, same era.
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
Cer, D.; Diab, M.; Agirre, E.; Lopez-Gazpio, I.; and Specia, L. 2017 · 2017
Cited alongside, same era.
Momentum Contrast for Unsupervised Visual Representation Learning
He, K.; Fan, H.; Wu, Y.; Xie, S.; and Girshick, R. 2020 · 2020
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Supervised Contrastive Learning
Khosla, P.; Teterwak, P.; Wang, C.; Sarna, A.; Tian, Y.; Isola, P.; Maschinot, A.; Liu, C.; and Krishnan, D. 2020 · 2020
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End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Miech, A.; Alayrac, J.-B.; Smaira, L.; Laptev, I.; Sivic, J.; and Zisserman, A. 2020 · 2020
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Self-Supervised Learning of Pretext-Invariant Representations
Misra, I.; and van der Maaten, L. 2020 · 2020
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Detecting out-of-distribution examples with gram matrices
Sastry, C. S.; and Oore, S. 2020 · 2020
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Contrastive Multiview Coding
Tian, Y.; Krishnan, D.; and Isola, P. 2020 · 2020
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Kay, W.; Carreira, J.; Simonyan, K.; Zhang, B.; Hillier, C.; Vijayanarasimhan, S.; Viola, F.; Green, T.; Back, T.; Natsev, P.; Suleyman, M.; and Zisserman, A. 2017 · 2017
Cited alongside, same era.
Deep metric learning with hierarchical triplet loss
Ge, W. 2018 · 2018
Cited alongside, same era.
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
Hara, K.; Kataoka, H.; and Satoh, Y. 2018 · 2018
Cited alongside, same era.
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Lee, K.; Lee, K.; Lee, H.; and Shin, J. 2018 · 2018
Cited alongside, same era.
RESOUND: Towards Action Recognition without Representation Bias
Li, Y.; Li, Y.; and Vasconcelos, N. 2018 · 2018
Cited alongside, same era.
Enhancing the reliability of out-of-distribution image detection in neural networks
Liang, S.; Li, Y.; and Srikant, R. 2018 · 2018
Cited alongside, same era.
Representation Learning with Contrastive Predictive Coding
van den Oord, A.; Li, Y.; and Vinyals, O. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Unsupervised Learning of Video Representations via Dense Trajectory Clustering
Tokmakov, P.; Hebert, M.; and Schmid, C. 2020 · 2020
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Self-Supervised Learning of Video-Induced Visual Invariances
Tschannen, M.; Djolonga, J.; Ritter, M.; Mahendran, A.; Houlsby, N.; Gelly, S.; and Lucic, M. 2020 · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Wang, T.; and Isola, P. 2020 · 2020
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Unsupervised Learning From Video With Deep Neural Embeddings
Zhuang, C.; She, T.; Andonian, A.; Mark, M. S.; and Yamins, D. 2020 · 2020
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Unsupervised Video Representation Learning by Bidirectional Feature Prediction
Behrmann, N.; Gall, J.; and Noroozi, M. 2021 · 2021
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Exploring simple siamese representation learning
Chen, X.; and He, K. 2021 · 2021
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TCLR: Temporal Contrastive Learning for Video Representation
Dave, I.; Gupta, R.; Rizve, M. N.; and Shah, M. 2021 · 2021
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A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
Feichtenhofer, C.; Fan, H.; Xiong, B.; Girshick, R.; and He, K. 2021 · 2021
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Semantically-Conditioned Negative Samples for Efficient Contrastive Learning
Neill, J. O.; and Bollegala, D. 2021 · 2021
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Representation Learning From Videos In-the-Wild: An Object-Centric Approach
Romijnders, R.; Mahendran, A.; Tschannen, M.; Djolonga, J.; Ritter, M.; Houlsby, N.; and Lucic, M. 2021 · 2021
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Understanding the Behaviour of Contrastive Loss
Wang, F.; and Liu, H. 2021 · 2021
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What Makes Instance Discrimination Good for Transfer Learning?
Zhao, N.; Wu, Z.; Lau, R. W. H.; and Lin, S. 2021 · 2021
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