Domain adaptation (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Domain adaptation" in English language version.

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8doi.org

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5arxiv.org

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4semanticscholar.org

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4github.com

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2jmlr.org

low place

1youtube.com

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1nips.cc

low place

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1researchgate.net

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1ed.ac.uk

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1handle.net

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1nih.gov

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1acm.org

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acm.org

dl.acm.org

Arief-Ang, I.B.; Salim, F.D.; Hamilton, M. (2017-11-08). DA-HOC: semi-supervised domain adaptation for room occupancy prediction using CO2 sensor data. 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys). Delft, Netherlands. pp. 1–10. doi:10.1145/3137133.3137146. ISBN 978-1-4503-5544-5.

arxiv.org

Kouw, Wouter M.; Loog, Marco (2019-01-14), An introduction to domain adaptation and transfer learning, doi:10.48550/arXiv.1812.11806, retrieved 2024-12-22
Farahani, Abolfazl; Voghoei, Sahar; Rasheed, Khaled; Arabnia, Hamid R. (2020-10-07), A Brief Review of Domain Adaptation, doi:10.48550/arXiv.2010.03978, retrieved 2024-12-23
Farahani, Abolfazl; Voghoei, Sahar; Rasheed, Khaled; Arabnia, Hamid R. (2020-10-07), A Brief Review of Domain Adaptation, doi:10.48550/arXiv.2010.03978, retrieved 2024-12-23
Hajiramezanali, Ehsan; Siamak Zamani Dadaneh; Karbalayghareh, Alireza; Zhou, Mingyuan; Qian, Xiaoning (2017). "Addressing Appearance Change in Outdoor Robotics with Adversarial Domain Adaptation". arXiv:1703.01461 [cs.RO].
Hajiramezanali, Ehsan; Siamak Zamani Dadaneh; Karbalayghareh, Alireza; Zhou, Mingyuan; Qian, Xiaoning (2018). "Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data". arXiv:1810.09433 [stat.ML].

doi.org

Sun, Shiliang; Shi, Honglei; Wu, Yuanbin (July 2015). "A survey of multi-source domain adaptation". Information Fusion. 24: 84–92. doi:10.1016/j.inffus.2014.12.003. S2CID 18385140.
Kouw, Wouter M.; Loog, Marco (2019-01-14), An introduction to domain adaptation and transfer learning, doi:10.48550/arXiv.1812.11806, retrieved 2024-12-22
Farahani, Abolfazl; Voghoei, Sahar; Rasheed, Khaled; Arabnia, Hamid R. (2020-10-07), A Brief Review of Domain Adaptation, doi:10.48550/arXiv.2010.03978, retrieved 2024-12-23
Farahani, Abolfazl; Voghoei, Sahar; Rasheed, Khaled; Arabnia, Hamid R. (2020-10-07), A Brief Review of Domain Adaptation, doi:10.48550/arXiv.2010.03978, retrieved 2024-12-23
Shimodaira, Hidetoshi (2000). "Improving predictive inference under covariate shift by weighting the log-likelihood function". Journal of Statistical Planning and Inference. 90 (2): 227–244. doi:10.1016/S0378-3758(00)00115-4. S2CID 9238949.
Gallego, A.J.; Calvo-Zaragoza, J.; Fisher, R.B. (2020). "Incremental Unsupervised Domain-Adversarial Training of Neural Networks" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (11): 4864–4878. doi:10.1109/TNNLS.2020.3025954. hdl:20.500.11820/72ba0443-8a7d-4cdd-8212-38682d4f0730. PMID 33027004. S2CID 210164756.
Arief-Ang, I.B.; Salim, F.D.; Hamilton, M. (2017-11-08). DA-HOC: semi-supervised domain adaptation for room occupancy prediction using CO2 sensor data. 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys). Delft, Netherlands. pp. 1–10. doi:10.1145/3137133.3137146. ISBN 978-1-4503-5544-5.
Arief-Ang, I.B.; Hamilton, M.; Salim, F.D. (2018-12-01). "A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data". ACM Transactions on Sensor Networks. 14 (3–4): 21:1–21:28. doi:10.1145/3217214. S2CID 54066723.

ed.ac.uk

pure.ed.ac.uk

Gallego, A.J.; Calvo-Zaragoza, J.; Fisher, R.B. (2020). "Incremental Unsupervised Domain-Adversarial Training of Neural Networks" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (11): 4864–4878. doi:10.1109/TNNLS.2020.3025954. hdl:20.500.11820/72ba0443-8a7d-4cdd-8212-38682d4f0730. PMID 33027004. S2CID 210164756.

github.com

Gnassounou, Théo and Kachaiev, Oleksii and Flamary, Rémi and Collas, Antoine and Lalou, Yanis and de Mathelin, Antoine and Gramfort, Alexandre and Bueno, Ruben and Michel, Florent and Mellot, Apolline and Loison, Virginie and Odonnat, Ambroise and Moreau, Thomas (2024) "SKADA : Scikit Adaptation"
de Mathelin, Antoine and Deheeger, François and Richard, Guillaume and Mougeot, Mathilde and Vayatis, Nicolas (2020) "ADAPT: Awesome Domain Adaptation Python Toolbox"
Mingsheng Long Junguang Jiang, Bo Fu. (2020) "Transfer-learning-library"
Ke Yan. (2016) "Domain adaptation toolbox"

handle.net

hdl.handle.net

Gallego, A.J.; Calvo-Zaragoza, J.; Fisher, R.B. (2020). "Incremental Unsupervised Domain-Adversarial Training of Neural Networks" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (11): 4864–4878. doi:10.1109/TNNLS.2020.3025954. hdl:20.500.11820/72ba0443-8a7d-4cdd-8212-38682d4f0730. PMID 33027004. S2CID 210164756.

jmlr.org

Crammer, Koby; Kearns, Michael; Wortman, Jeniifer (2008). "Learning from Multiple Sources" (PDF). Journal of Machine Learning Research. 9: 1757–1774.
Ganin, Yaroslav; Ustinova, Evgeniya; Ajakan, Hana; Germain, Pascal; Larochelle, Hugo; Laviolette, François; Marchand, Mario; Lempitsky, Victor (2016). "Domain-Adversarial Training of Neural Networks" (PDF). Journal of Machine Learning Research. 17: 1–35.

nih.gov

pubmed.ncbi.nlm.nih.gov

Gallego, A.J.; Calvo-Zaragoza, J.; Fisher, R.B. (2020). "Incremental Unsupervised Domain-Adversarial Training of Neural Networks" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (11): 4864–4878. doi:10.1109/TNNLS.2020.3025954. hdl:20.500.11820/72ba0443-8a7d-4cdd-8212-38682d4f0730. PMID 33027004. S2CID 210164756.

nips.cc

papers.nips.cc

Huang, Jiayuan; Smola, Alexander J.; Gretton, Arthur; Borgwardt, Karster M.; Schölkopf, Bernhard (2006). "Correcting Sample Selection Bias by Unlabeled Data" (PDF). Conference on Neural Information Processing Systems (NIPS). pp. 601–608.

researchgate.net

Shimodaira, Hidetoshi (2000). "Improving predictive inference under covariate shift by weighting the log-likelihood function". Journal of Statistical Planning and Inference. 90 (2): 227–244. doi:10.1016/S0378-3758(00)00115-4. S2CID 9238949.

semanticscholar.org

api.semanticscholar.org

Sun, Shiliang; Shi, Honglei; Wu, Yuanbin (July 2015). "A survey of multi-source domain adaptation". Information Fusion. 24: 84–92. doi:10.1016/j.inffus.2014.12.003. S2CID 18385140.
Shimodaira, Hidetoshi (2000). "Improving predictive inference under covariate shift by weighting the log-likelihood function". Journal of Statistical Planning and Inference. 90 (2): 227–244. doi:10.1016/S0378-3758(00)00115-4. S2CID 9238949.
Gallego, A.J.; Calvo-Zaragoza, J.; Fisher, R.B. (2020). "Incremental Unsupervised Domain-Adversarial Training of Neural Networks" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (11): 4864–4878. doi:10.1109/TNNLS.2020.3025954. hdl:20.500.11820/72ba0443-8a7d-4cdd-8212-38682d4f0730. PMID 33027004. S2CID 210164756.
Arief-Ang, I.B.; Hamilton, M.; Salim, F.D. (2018-12-01). "A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data". ACM Transactions on Sensor Networks. 14 (3–4): 21:1–21:28. doi:10.1145/3217214. S2CID 54066723.

youtube.com

Stanford Online (2023-04-11). Stanford CS330 Deep Multi-Task & Meta Learning - Domain Adaptation l 2022 I Lecture 13. Retrieved 2024-12-23 – via YouTube.