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Multi-Source Domain Adaptation (MSDA) deals with the transfer of task knowledge from multiple labeled source domains to an unlabeled target domain, under a domain-shift.
“Analysis of representations for domain adaptation”
Shai Ben-David, John Blitzer, Koby Crammer and Fernando Pereira · 2007
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“Caltech-256 object category dataset”
Gregory Griffin, Alex Holub and Pietro Perona · 2007
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“Visualizing data using t-SNE”
Laurens Maaten and Geoffrey Hinton · 2008
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“Curriculum learning”
Yoshua Bengio, Jérôme Louradour, Ronan Collobert and Jason Weston · 2009
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“Domain adaptation with multiple sources”
Yishay Mansour, Mehryar Mohri and Afshin Rostamizadeh · 2009
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“A theory of learning from different domains”
Shai Ben-David et al · 2010
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“The Pascal Visual Object Classes (VOC) Challenge”
M. Everingham et al · 2010
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“Domain adaptation via transfer component analysis”
Sinno Pan, Ivor Tsang, James Kwok and Qiang Yang · 2010
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“Adapting visual category models to new domains”
Kate Saenko, Brian Kulis, Mario Fritz and Trevor Darrell · 2010
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“Co-training for domain adaptation”
Minmin Chen, Kilian Weinberger and John Blitzer · 2011
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“Unbiased look at dataset bias”
Antonio Torralba and Alexei Efros · 2011
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“Geodesic flow kernel for unsupervised domain adaptation”
Boqing Gong, Yuan Shi, Fei Sha and Kristen Grauman · 2012
Earlier work this paper cites.
“Multiple source adaptation and the Rényi divergence”
Yishay Mansour, Mehryar Mohri and Afshin Rostamizadeh · 2012
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“Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks”
Dong-Hyun Lee · 2013
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“Generative adversarial nets”
Ian Goodfellow et al · 2014
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“Adam: A method for stochastic optimization”
Diederik Kingma and Jimmy Ba · 2014
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“Learning and transferring mid-level image representations using convolutional neural networks”
Maxime Oquab, Leon Bottou, Ivan Laptev and Josef Sivic · 2014
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“Deep domain confusion: Maximizing for domain invariance”
Eric Tzeng et al · 2014
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“How transferable are features in deep neural networks?”
Jason Yosinski, Jeff Clune, Yoshua Bengio and Hod Lipson · 2014
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“Unsupervised Domain Adaptation by Backpropagation”
Yaroslav Ganin and Victor Lempitsky · 2015
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“Learning Transferable Features with Deep Adaptation Networks”
Mingsheng Long, Yue Cao, Jianmin Wang and Michael Jordan · 2015
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“Imagenet large scale visual recognition challenge”
Olga Russakovsky et al · 2015
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“Simultaneous deep transfer across domains and tasks”
Eric Tzeng, Judy Hoffman, Trevor Darrell and Kate Saenko · 2015
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“Distribution-Matching Embedding for Visual Domain Adaptation”
Mahsa Baktashmotlagh, Mehrtash Harandi and Mathieu Salzmann · 2016
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“Deep residual learning for image recognition”
Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun · 2016
Cited alongside, same era.
“Unsupervised domain adaptation with residual transfer networks”
Mingsheng Long, Han Zhu, Jianmin Wang and Michael Jordan · 2016
Cited alongside, same era.
“Deep coral: Correlation alignment for deep domain adaptation”
Baochen Sun and Kate Saenko · 2016
Cited alongside, same era.
“Deep transfer learning with joint adaptation networks”
Mingsheng Long, Han Zhu, Jianmin Wang and Michael Jordan · 2017
Cited alongside, same era.
“Knowledge adaptation: Teaching to adapt”
Sebastian Ruder, Parsa Ghaffari and John Breslin · 2017
Cited alongside, same era.
“Asymmetric Tri-training for Unsupervised Domain Adaptation”
Kuniaki Saito, Yoshitaka Ushiku and Tatsuya Harada · 2017
“Unsupervised domain adaptation for semantic segmentation via class-balanced self-training”
Yang Zou, Zhiding Yu, BVK Vijaya and Jinsong Wang · 2018
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“Domain-Specific Batch Normalization for Unsupervised Domain Adaptation”
Woong-Gi Chang et al · 2019
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“CrDoCo: Pixel-level domain transfer with cross-domain consistency”
Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang and Jia-Bin Huang · 2019
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“UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation”
Jogendra Kundu, Nishank Lakkakula and R Babu · 2019
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“Bidirectional learning for domain adaptation of semantic segmentation”
Yunsheng Li, Lu Yuan and Nuno Vasconcelos · 2019
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“Separate to Adapt: Open Set Domain Adaptation via Progressive Separation”
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Cited alongside, same era.
“Adversarial discriminative domain adaptation”
Eric Tzeng, Judy Hoffman, Kate Saenko and Trevor Darrell · 2017
Cited alongside, same era.
“Deep hashing network for unsupervised domain adaptation”
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty and Sethuraman Panchanathan · 2017
Cited alongside, same era.
“Partial transfer learning with selective adversarial networks”
Zhangjie Cao, Mingsheng Long, Jianmin Wang and Michael Jordan · 2018
Cited alongside, same era.
“Multi-Source Domain Adaptation with Mixture of Experts”
Jiang Guo, Darsh Shah and Regina Barzilay · 2018
Cited alongside, same era.
“Algorithms and theory for multiple-source adaptation”
Judy Hoffman, Mehryar Mohri and Ningshan Zhang · 2018
Cited alongside, same era.
“Cycada: Cycle-consistent adversarial domain adaptation”
Judy Hoffman et al · 2018
Cited alongside, same era.
Hong Liu et al · 2019
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“Transferrable prototypical networks for unsupervised domain adaptation”
Yingwei Pan et al · 2019
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“PyTorch: An Imperative Style, High-Performance Deep Learning Library”
Adam Paszke et al · 2019
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“Moment matching for multi-source domain adaptation”
Xingchao Peng et al · 2019
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“Unsupervised domain adaptation using feature-whitening and consensus loss”
Subhankar Roy et al · 2019
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“Universal Domain Adaptation”
Kaichao You et al · 2019
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“How does Disagreement Help Generalization against Label Corruption?”
Xingrui Yu et al · 2019
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“Category anchor-guided unsupervised domain adaptation for semantic segmentation”
Qiming Zhang, Jing Zhang, Wei Liu and Dacheng Tao · 2019
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“Aligning domain-specific distribution and classifier for cross-domain classification from multiple sources”
Yongchun Zhu, Fuzhen Zhuang and Deqing Wang · 2019
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“Confidence regularized self-training”
Yang Zou et al · 2019
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“Class-Incremental Domain Adaptation”
Jogendra Kundu et al · 2020
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“Universal Source-Free Domain Adaptation”
Jogendra Kundu, Naveen Venkat, Rahul M and R. Babu · 2020
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“Towards Inheritable Models for Open-Set Domain Adaptation”
Jogendra Kundu et al · 2020
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“Self: Learning to filter noisy labels with self-ensembling”
Duc Nguyen et al · 2020
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“Universal domain adaptation through self supervision”
Kuniaki Saito, Donghyun Kim, Stan Sclaroff and Kate Saenko · 2020
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“Fixmatch: Simplifying semi-supervised learning with consistency and confidence”
Kihyuk Sohn et al · 2020
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“Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey”
Sicheng Zhao, Bo Li, Pengfei Xu and Kurt Keutzer · 2020
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“Domain-adversarial training of neural networks”
Yaroslav Ganin et al · 2030
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