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Central to active learning (AL) is what data should be selected for annotation.
Deep Active Learning with Adaptive Acquisition
Haußmann, M.; Hamprecht, F. A.; and Kandemir, M. 2019 · 1906
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Toward Optimal Active Learning through Monte Carlo Estimation of Error Reduction
Roy, N.; and McCallum, A. 2001 · 2001
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Active Learning Using Pre-Clustering
Nguyen, H. T.; and Smeulders, A. 2004 · 2004
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Semi-Supervised Learning by Entropy Minimization
Grandvalet, Y.; Bengio, Y.; et al. 2005 · 2005
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One-Shot Learning of Object Categories
Fei-Fei, L.; Fergus, R.; and Perona, P. 2006 · 2006
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Multiple-Instance Active Learning
Settles, B.; Craven, M.; and Ray, S. 2007 · 2007
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Link-based Active Learning
Bilgic, M.; and Getoor, L. 2009 · 2009
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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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Large-Scale Machine Learning with Stochastic Gradient Descent
Bottou, L. 2010 · 2010
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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 · 2011
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Maximizing Expected Model Change for Active Learning in Regression
Cai, W.; Zhang, Y.; and Zhou, J. 2013 · 2013
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A Convex Optimization Framework for Active Learning
Elhamifar, E.; Sapiro, G.; Yang, A.; and Shankar Sasrty, S. 2013 · 2013
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Auto-Encoding Variational Bayes
Kingma, D. P.; and Welling, M. 2013 · 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 · 2014
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2014 · 2014
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Hierarchical Subquery Evaluation for Active Learning on A Graph
Mac Aodha, O.; Campbell, N. D.; Kautz, J.; and Brostow, G. J. 2014 · 2014
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Context Aware Active Learning of Activity Recognition Models
Hasan, M.; and Roy-Chowdhury, A. K. 2015 · 2015
Cited alongside, same era.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K.; and Zisserman, A. 2015 · 2015
Cited alongside, same era.
Multi-Class Active Learning by Uncertainty Sampling with Diversity Maximization
Yang, Y.; Ma, Z.; Nie, F.; Chang, X.; and Hauptmann, A. G. 2015 · 2015
Cited alongside, same era.
The Cityscapes Dataset for Semantic Urban Scene Understanding
Cordts, M.; Omran, M.; Ramos, S.; Rehfeld, T.; Enzweiler, M.; Benenson, R.; Franke, U.; Roth, S.; and Schiele, B. 2016 · 2016
Cited alongside, same era.
Dropout as A Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Gal, Y.; and Ghahramani, Z. 2016 · 2016
Cited alongside, same era.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
The Power of Ensembles for Active Learning in Image Classification
Beluch, W. H.; Genewein, T.; Nürnberger, A.; and Köhler, J. M. 2018 · 2018
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Adversarial Active Learning for Deep Networks: a Margin Based Approach
Ducoffe, M.; and Precioso, F. 2018 · 2018
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Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Kuo, W.; Häne, C.; Yuh, E.; Mukherjee, P.; and Malik, J. 2018 · 2018
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Visualizing the Loss Landscape of Neural Nets
Li, H.; Xu, Z.; Taylor, G.; Studer, C.; and Goldstein, T. 2018 · 2018
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Efficient Active Learning for Image Classification and Segmentation Using A Sample Selection and Conditional Generative Adversarial Network
Mahapatra, D.; Bozorgtabar, B.; Thiran, J.-P.; and Reyes, M. 2018 · 2018
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Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2016 · 2016
Cited alongside, same era.
Active Learning for Classification with Maximum Model Change
Cai, W.; Zhang, Y.; Zhang, Y.; Zhou, S.; Wang, W.; Chen, Z.; and Ding, C. 2017 · 2017
Cited alongside, same era.
Convolutional Neural Networks for Automated Annotation of Cellular Cryo-Electron Tomograms
Chen, M.; Dai, W.; Sun, S. Y.; Jonasch, D.; He, C. Y.; Schmid, M. F.; Chiu, W.; and Ludtke, S. J. 2017 · 2017
Cited alongside, same era.
Deep Bayesian Active Learning with Image Data
Gal, Y.; Islam, R.; and Ghahramani, Z. 2017 · 2017
Cited alongside, same era.
Cost-Effective Active Learning for Melanoma Segmentation
Gorriz, M.; Carlier, A.; Faure, E.; and Giro-i Nieto, X. 2017 · 2017
Cited alongside, same era.
Understanding Black-box Predictions via Influence Functions
Koh, P. W.; and Liang, P. 2017 · 2017
Cited alongside, same era.
Active Learning for Convolutional Neural Networks: A Core-Set Approach
Sener, O.; and Savarese, S. 2018 · 2018
Later among the works it cites.
Knowledge Transfer with Jacobian Matching
Srinivas, S.; and Fleuret, F. 2018 · 2018
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MixMatch: A Holistic Approach to Semi-Supervised Learning
Berthelot, D.; Carlini, N.; Goodfellow, I.; Papernot, N.; Oliver, A.; and Raffel, C. A. 2019 · 2019
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SHREC’19 Track: Classification in Cryo-Electron Tomograms
Gubins, I.; van der Shot, G.; Veltkamp, R.; Foerster, F.; Du, X.; Zeng, X.; et al. 2019 · 2019
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Variational Adversarial Active Learning
Sinha, S.; Ebrahimi, S.; and Darrell, T. 2019 · 2019
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Learning Loss for Active Learning
Yoo, D.; and Kweon, I. S. 2019 · 2019
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A General Framework for Uncertainty Estimation in Deep Learning
Loquercio, A.; Segu, M.; and Scaramuzza, D. 2020 · 2020
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Adversarial Sampling for Active Learning
Mayer, C.; and Timofte, R. 2020 · 2020
Later among the works it cites.
State-Relabeling Adversarial Active Learning
Zhang, B.; Li, L.; Yang, S.; Wang, S.; Zha, Z.-J.; and Huang, Q. 2020 · 2020
Later among the works it cites.
Sequential Graph Convolutional Network for Active Learning
Caramalau, R.; Bhattarai, B.; and Kim, T.-K. 2021 · 2021
Closest in time.
Influence Selection for Active Learning
Liu, Z.; Ding, H.; Zhong, H.; Li, W.; Dai, J.; and He, C. 2021 · 2021
Closest in time.