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Unsupervised domain adaptation has recently emerged as an effective paradigm for generalizing deep neural networks to new target domains.
Discriminative Active Learning
Gissin, D.; and Shalev-Shwartz, S. 2019 · 1907
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Less is More: Active Learning with Support Vector Machines
Schohn, G.; and Cohn, D. 2000 · 2000
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CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Hoffman, J.; Tzeng, E.; Park, T.; Zhu, J.; Isola, P.; Saenko, K.; Efros, A. A.; and Darrell, T. 2018 · 2003
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Does active learning work? A review of the research
Prince, M. 2004 · 2004
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A tutorial on energy-based learning
LeCun, Y.; Chopra, S.; Hadsell, R.; Ranzato, M.; and Huang, F. 2006 · 2006
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k-means++: the advantages of careful seeding
Arthur, D.; and Vassilvitskii, S. 2007 · 2007
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Domain Adaptation with Active Learning for Word Sense Disambiguation
Chan, Y. S.; and Ng, H. T. 2007 · 2007
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A kernel method for the two-sample-problem
Gretton, A.; Borgwardt, K. M.; Rasch, M.; Schölkopf, B.; and Smola, A. J. 2007 · 2007
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Discriminative Learning Under Covariate Shift
Bickel, S.; Brückner, M.; and Scheffer, T. 2009 · 2009
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Multi-class active learning for image classification
Joshi, A. J.; Porikli, F.; and Papanikolopoulos, N. 2009 · 2009
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Active learning literature survey
Settles, B. 2009 · 2009
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A survey on transfer learning
Pan, S. J.; and Yang, Q. 2010 · 2010
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Domain adaptation meets active learning
Rai, P.; Saha, A.; Daumé III, H.; and Venkatasubramanian, S. 2010 · 2010
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Adapting visual category models to new domains
Saenko, K.; Kulis, B.; Fritz, M.; and Darrell, T. 2010 · 2010
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Two faces of active learning
Dasgupta, S. 2011 · 2011
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Joint Transfer and Batch-mode Active Learning
Chattopadhyay, R.; Fan, W.; Davidson, I.; Panchanathan, S.; and Ye, J. 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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Theory of disagreement-based active learning
Hanneke, S. 2014 · 2014
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A new active labeling method for deep learning
Wang, D.; and Shang, Y. 2014 · 2014
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Convex Optimization: Algorithms and Complexity
Bubeck, S. 2015 · 2015
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Unsupervised Domain Adaptation by Backpropagation
Ganin, Y.; and Lempitsky, V. 2015 · 2015
Cited alongside, same era.
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O.; Fischer, P.; and Brox, T. 2015 · 2015
Cited alongside, same era.
Simultaneous Deep Transfer Across Domains and Tasks
Tzeng, E.; Hoffman, J.; Darrell, T.; and Saenko, K. 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.
Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Cited alongside, same era.
Playing for data: Ground truth from computer games
Richter, S. R.; Vineet, V.; Roth, S.; and Koltun, V. 2016 · 2016
Cited alongside, same era.
Transferable Representation Learning with Deep Adaptation Networks
Long, M.; Cao, Y.; Cao, Z.; Wang, J.; and Jordan, M. I. 2019 · 2019
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PyTorch: An imperative style, high-performance deep learning library
Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; et al. 2019 · 2019
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Semi-Supervised Domain Adaptation via Minimax Entropy
Saito, K.; Kim, D.; Sclaroff, S.; Darrell, T.; and Saenko, K. 2019 · 2019
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Variational Adversarial Active Learning
Sinha, S.; Ebrahimi, S.; and Darrell, T. 2019 · 2019
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Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
Xu, R.; Li, G.; Yang, J.; and Lin, L. 2019 · 2019
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WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving
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Learning Algorithms for Active Learning
Bachman, P.; Sordoni, A.; and Trischler, A. 2017 · 2017
Cited alongside, same era.
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
Bousmalis, K.; Silberman, N.; Dohan, D.; Erhan, D.; and Krishnan, D. 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.
Deep Transfer Learning with Joint Adaptation Networks
Long, M.; Zhu, H.; Wang, J.; and Jordan, M. I. 2017 · 2017
Cited alongside, same era.
VisDA: The Visual Domain Adaptation Challenge
Peng, X.; Usman, B.; Kaushik, N.; Hoffman, J.; Wang, D.; and Saenko, K. 2017 · 2017
Cited alongside, same era.
Adversarial discriminative domain adaptation
Tzeng, E.; Hoffman, J.; Saenko, K.; and Darrell, T. 2017 · 2017
Cited alongside, same era.
Yogamani, S. K.; Witt, C.; Rashed, H.; Nayak, S.; Mansoor, S.; Varley, P.; Perrotton, X.; O’Dea, D.; Pérez, P.; Hughes, C.; Horgan, J.; Sistu, G.; Chennupati, S.; Uricár, M.; Milz, S.; Simon, M.; and Amende, K. 2019 · 2019
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Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Ash, J. T.; Zhang, C.; Krishnamurthy, A.; Langford, J.; and Agarwal, A. 2020 · 2020
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Your classifier is secretly an energy based model and you should treat it like one
Grathwohl, W.; Wang, K.; Jacobsen, J.; Duvenaud, D.; Norouzi, M.; and Swersky, K. 2020 · 2020
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Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
Kang, G.; Wei, Y.; Yang, Y.; Zhuang, Y.; and Hauptmann, A. G. 2020 · 2020
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Domain Conditioned Adaptation Network
Li, S.; Liu, H. C.; Lin, Q.; Xie, B.; Ding, Z.; Huang, G.; and Tang, J. 2020 · 2020
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Energy-based Out-of-distribution Detection
Liu, W.; Wang, X.; Owens, J. D.; and Li, Y. 2020 · 2020
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Deep Active Learning: Unified and Principled Method for Query and Training
Shui, C.; Zhou, F.; Gagné, C.; and Wang, B. 2020 · 2020
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Active Adversarial Domain Adaptation
Su, J.; Tsai, Y.; Sohn, K.; Liu, B.; Maji, S.; and Chandraker, M. 2020 · 2020
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Few-shot Domain Adaptation by Causal Mechanism Transfer
Teshima, T.; Sato, I.; and Sugiyama, M. 2020 · 2020
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Transferable Query Selection for Active Domain Adaptation
Fu, B.; Cao, Z.; Wang, J.; and Long, M. 2021 · 2021
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Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings
Prabhu, V.; Chandrasekaran, A.; Saenko, K.; and Hoffman, J. 2021 · 2021
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Unsupervised Energy-based Adversarial Domain Adaptation for Cross-domain Text Classification
Zou, H.; Yang, J.; and Wu, X. 2021 · 2021
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Discrepancy-Based Active Learning for Domain Adaptation
mathelin, A. D.; Deheeger, F.; MOUGEOT, M.; and Vayatis, N. 2022 · 2022
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Geodesic flow kernel for unsupervised domain adaptation
Gong, B.; Shi, Y.; Sha, F.; and Grauman, K. 2012 · 2073
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