Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data | Paper Citation Record

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This paper cites Molecular Systems Biology 12(7), 878 (2016) https://www.embopress.org/doi/pdf/10.15252/msb.20156651.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Molecular Systems Biology 12(7), 878 (2016) https://www.embopress.org/doi/pdf/10.15252/msb.20156651

Reference 1

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This paper cites Nature reviews Molecular cell biology 23(1), 40–55 (2022).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nature reviews Molecular cell biology 23(1), 40–55 (2022)

Reference 2

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This paper cites Nucleic Acids Research 50(W1), 228–234 (2022) https://doi.org/10.1093/nar/gkac278 https://academic.oup.com/nar/article- pdf/50/W1/W228/44378499/gkac278.pdf.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nucleic Acids Research 50(W1), 228–234 (2022) https://doi.org/10.1093/nar/gkac278 https://academic.oup.com/nar/article- pdf/50/W1/W228/44378499/gkac278.pdf

Reference 3

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This paper cites Artificial Intelligence in Medicine 45(2), 91–96 (2009) https://doi.org/10.1016/j.artmed.2008.08.014.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Artificial Intelligence in Medicine 45(2), 91–96 (2009) https://doi.org/10.1016/j.artmed.2008.08.014

Reference 4

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This paper cites Science Advances 10(51), 6040 (2024) https://doi.org/10.1126/sciadv.adp6040 https://www.science.org/doi/pdf/10.1126/sciadv.adp6040.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Science Advances 10(51), 6040 (2024) https://doi.org/10.1126/sciadv.adp6040 https://www.science.org/doi/pdf/10.1126/sciadv.adp6040

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This paper cites Advances in data science and information engineering: proceedings from ICDATA 2020 and IKE 2020, 877–894 (2021).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in data science and information engineering: proceedings from ICDATA 2020 and IKE 2020, 877–894 (2021)

Reference 6

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 7

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This paper cites Federated Adversarial Domain Adaptation.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Federated Adversarial Domain Adaptation

Reference 8

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This paper cites In: Proceed- ings of the AAAI Conference on Artificial Intelligence, vol.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceed- ings of the AAAI Conference on Artificial Intelligence, vol

Reference 9

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 44(11), 8602–8617 (2021).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data IEEE Transactions on Pattern Analysis and Machine Intelligence 44(11), 8602–8617 (2021)

Reference 10

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This paper cites In: International Conference on Machine Learning, pp.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: International Conference on Machine Learning, pp

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.784326Z

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This paper cites Advances in neural information processing systems 29 (2016).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in neural information processing systems 29 (2016)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.775194Z

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This paper cites In: Meila, M., Zhang, T.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Meila, M., Zhang, T

Reference 13

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This paper cites Advances in neural information processing systems 29 (2016).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in neural information processing systems 29 (2016)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.758565Z

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This paper cites Nature biomedical engineering 2(3), 158–164 (2018).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nature biomedical engineering 2(3), 158–164 (2018)

Reference 15

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This paper cites Nature biomedical engineering 2(10), 749–760 (2018).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nature biomedical engineering 2(10), 749–760 (2018)

Reference 16

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This paper cites Nature Biomedical Engineering 6(12), 1353–1369 (2022).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nature Biomedical Engineering 6(12), 1353–1369 (2022)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.736353Z

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This paper cites Nature genetics 45(10), 1113–1120 (2013).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nature genetics 45(10), 1113–1120 (2013)

Reference 18

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This paper cites Nucleic acids research 30(1), 207–210 (2002).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Nucleic acids research 30(1), 207–210 (2002)

Reference 19

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This paper cites Bioinformatics 35(14), 154–163 (2019).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Bioinformatics 35(14), 154–163 (2019)

Reference 20

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This paper cites Genome biology 14, 1–20 (2013).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Genome biology 14, 1–20 (2013)

Reference 21

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.692605Z

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data 2 3 4 Castel Stephane E

Reference 23

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This paper cites PLoS biology 3(9), 274 (2005).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data PLoS biology 3(9), 274 (2005)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.673054Z

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This paper cites Advances in Neural Information Processing Systems 36, 26991–27004 (2023).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in Neural Information Processing Systems 36, 26991–27004 (2023)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.663138Z

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This paper cites Neurocomputing 312, 135–153 (2018).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Neurocomputing 312, 135–153 (2018)

Reference 26

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This paper cites In: International Conference on Machine Learning, pp.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: International Conference on Machine Learning, pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.647293Z

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This paper cites Advances in Neural Information Processing Systems 36, 74127–74139 (2023).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in Neural Information Processing Systems 36, 74127–74139 (2023)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.637625Z

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This paper cites Journal of machine learning research 17(59), 1–35 (2016).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Journal of machine learning research 17(59), 1–35 (2016)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.628114Z

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This paper cites In: International Conference on Machine Learning, pp.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: International Conference on Machine Learning, pp

Reference 30

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This paper cites Advances in neural information processing systems 31 (2018).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in neural information processing systems 31 (2018)

Reference 31

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in Neural Information Processing Systems 35, 10040–10054 (2022)

Reference 32

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Advances in Neural Information Processing Systems 34, 23309–23320 (2021)

Reference 33

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: The Twelfth International Conference 25 on Learning Representations (2024)

Reference 34

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Unresolved cited work

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Reference 36

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This paper cites International journal of neural systems 14(02), 69–106 (2004).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data International journal of neural systems 14(02), 69–106 (2004)

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: 2023 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), pp

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.540554Z

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data Practical Secure Aggregation for Federated Learning on User-Held Data

Reference 39

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data BMC genomics 17, 1–10 (2016)

Reference 40

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Artificial Intelligence and Statistics, pp

Reference 41

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Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data https://github.com/ SheffieldML/GPy

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.508837Z

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Observation daccd250-a4d5-4754-b63e-5b03407c17c9 · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence (2023).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceedings of the AAAI Conference on Artificial Intelligence (2023)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.500636Z

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This paper cites In: Proceedings of the International Conference on Machine Learning (ICML) (2021).

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceedings of the International Conference on Machine Learning (ICML) (2021)

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.492031Z

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This paper cites In: Proceedings of the International Conference on Machine Learning (ICML) (2022) 26.

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data In: Proceedings of the International Conference on Machine Learning (ICML) (2022) 26

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:25:54.483571Z

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