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Material Type: Article
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Natural language inference model for customer advocacy detection in online customer engagementMachine learning, 2024-04, Vol.113 (4), p.2249-2275 [Peer Reviewed Journal]The Author(s) 2023 ;The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-023-06476-wDigital Resources/Online E-Resources |
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Material Type: Article
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TOCOL: improving contextual representation of pre-trained language models via token-level contrastive learningMachine learning, 2024, Vol.113 (7), p.3999-4012 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-023-06512-9Digital Resources/Online E-Resources |
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3 |
Material Type: Article
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Machine learning from casual conversationMachine learning, 2023-12, Vol.112 (12), p.4789-4836 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-023-06383-0Digital Resources/Online E-Resources |
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4 |
Material Type: Article
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OWL2Vec: embedding of OWL ontologiesMachine learning, 2021-07, Vol.110 (7), p.1813-1845 [Peer Reviewed Journal]The Author(s) 2021 ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-021-05997-6Full text available |
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5 |
Material Type: Article
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Regularisation of neural networks by enforcing Lipschitz continuityMachine learning, 2021-02, Vol.110 (2), p.393-416 [Peer Reviewed Journal]The Author(s) 2020 ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-020-05929-wFull text available |
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Material Type: Article
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A survey on semi-supervised learningMachine learning, 2020-02, Vol.109 (2), p.373-440 [Peer Reviewed Journal]The Author(s) 2019 ;Machine Learning is a copyright of Springer, (2019). All Rights Reserved. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-019-05855-6Full text available |
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Material Type: Article
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Scalable Bayesian preference learning for crowdsMachine learning, 2020-04, Vol.109 (4), p.689-718 [Peer Reviewed Journal]The Author(s) 2020 ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-019-05867-2Full text available |
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8 |
Material Type: Article
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High-dimensional Bayesian optimization using low-dimensional feature spacesMachine learning, 2020-09, Vol.109 (9-10), p.1925-1943 [Peer Reviewed Journal]The Author(s) 2020 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-020-05899-zFull text available |
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9 |
Material Type: Article
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Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methodsMachine learning, 2021-03, Vol.110 (3), p.457-506 [Peer Reviewed Journal]The Author(s) 2021 ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-021-05946-3Full text available |
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10 |
Material Type: Article
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Challenges of real-world reinforcement learning: definitions, benchmarks and analysisMachine learning, 2021-09, Vol.110 (9), p.2419-2468 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2021. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-021-05961-4Full text available |
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11 |
Material Type: Article
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Learning from positive and unlabeled data: a surveyMachine learning, 2020-04, Vol.109 (4), p.719-760 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-020-05877-5Full text available |
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Material Type: Article
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Unified SVM algorithm based on LS-DC lossMachine learning, 2023-08, Vol.112 (8), p.2975-3002 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2021. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-021-05996-7Digital Resources/Online E-Resources |
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13 |
Material Type: Article
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Gradient descent optimizes over-parameterized deep ReLU networksMachine learning, 2020-03, Vol.109 (3), p.467-492 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2019 ;Machine Learning is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-019-05839-6Full text available |
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14 |
Material Type: Article
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Adaptive random forests for evolving data stream classificationMachine learning, 2017-10, Vol.106 (9-10), p.1469-1495 [Peer Reviewed Journal]The Author(s) 2017 ;Machine Learning is a copyright of Springer, 2017. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-017-5642-8Full text available |
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15 |
Material Type: Article
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Multi-target regression via input space expansion: treating targets as inputsMachine learning, 2016-07, Vol.104 (1), p.55-98 [Peer Reviewed Journal]The Author(s) 2016 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-016-5546-zFull text available |
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Material Type: Article
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Temporal pattern attention for multivariate time series forecastingMachine learning, 2019-09, Vol.108 (8-9), p.1421-1441 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2019 ;Machine Learning is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-019-05815-0Full text available |
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17 |
Material Type: Article
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Optimal classification treesMachine learning, 2017-07, Vol.106 (7), p.1039-1082 [Peer Reviewed Journal]The Author(s) 2017 ;Machine Learning is a copyright of Springer, 2017. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-017-5633-9Full text available |
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18 |
Material Type: Article
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Utilising energy function and variational inference training for learning a graph neural network architectureMachine learning, 2024-03, Vol.113 (3), p.1219-1241 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-024-06513-2Digital Resources/Online E-Resources |
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19 |
Material Type: Article
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Can cross-domain term extraction benefit from cross-lingual transfer and nested term labeling?Machine learning, 2024, Vol.113 (7), p.4285-4314 [Peer Reviewed Journal]The Author(s) 2024 ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-023-06506-7Digital Resources/Online E-Resources |
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20 |
Material Type: Article
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Exposing and explaining fake news on-the-flyMachine learning, 2024, Vol.113 (7), p.4615-4637 [Peer Reviewed Journal]The Author(s) 2024 ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-024-06527-wDigital Resources/Online E-Resources |