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1
Regularisation of neural networks by enforcing Lipschitz continuity
Regularisation of neural networks by enforcing Lipschitz continuity
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Regularisation of neural networks by enforcing Lipschitz continuity

Machine 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-w

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2
Optimal classification trees
Optimal classification trees
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Optimal classification trees

Machine 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/s10994-017-5633-9

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3
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification
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autoBOT: evolving neuro-symbolic representations for explainable low resource text classification

Machine learning, 2021, Vol.110 (5), p.989-1028 [Peer Reviewed Journal]

The Author(s) 2021 ;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/s10994-021-05968-x ;PMID: 34720391

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4
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics
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Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics

Machine learning, 2023-10, Vol.112 (10), p.3713-3747 [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/s10994-021-06019-1

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5
Interpretable clustering: an optimization approach
Interpretable clustering: an optimization approach
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Interpretable clustering: an optimization approach

Machine learning, 2021, Vol.110 (1), p.89-138 [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/s10994-020-05896-2

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6
Understanding generalization error of SGD in nonconvex optimization
Understanding generalization error of SGD in nonconvex optimization
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Understanding generalization error of SGD in nonconvex optimization

Machine learning, 2022, Vol.111 (1), p.345-375 [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/s10994-021-06056-w

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7
Stronger data poisoning attacks break data sanitization defenses
Stronger data poisoning attacks break data sanitization defenses
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Stronger data poisoning attacks break data sanitization defenses

Machine learning, 2022, Vol.111 (1), p.1-47 [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/s10994-021-06119-y

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8
Maximum margin partial label learning
Maximum margin partial label learning
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Maximum margin partial label learning

Machine learning, 2017-04, Vol.106 (4), p.573-593 [Peer Reviewed Journal]

The Author(s) 2016 ;Machine Learning is a copyright of Springer, 2017. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-016-5606-4

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9
Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model
Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model
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Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model

Machine learning, 2013-06, Vol.91 (3), p.325-349 [Peer Reviewed Journal]

The Author(s) 2013 ;2014 INIST-CNRS ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-013-5368-1

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10
On label dependence and loss minimization in multi-label classification
On label dependence and loss minimization in multi-label classification
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On label dependence and loss minimization in multi-label classification

Machine learning, 2012-07, Vol.88 (1-2), p.5-45 [Peer Reviewed Journal]

The Author(s) 2012 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-012-5285-8

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11
Generalization bounds for metric and similarity learning
Generalization bounds for metric and similarity learning
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Generalization bounds for metric and similarity learning

Machine learning, 2016-01, Vol.102 (1), p.115-132 [Peer Reviewed Journal]

The Author(s) 2015 ;The Author(s) 2016 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-015-5499-7

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12
Imbalanced regression and extreme value prediction
Imbalanced regression and extreme value prediction
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Imbalanced regression and extreme value prediction

Machine learning, 2020-09, Vol.109 (9-10), p.1803-1835 [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/s10994-020-05900-9

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13
The voice of optimization
The voice of optimization
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The voice of optimization

Machine learning, 2021-02, Vol.110 (2), p.249-277 [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/s10994-020-05893-5

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14
Semi-supervised AUC optimization based on positive-unlabeled learning
Semi-supervised AUC optimization based on positive-unlabeled learning
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Semi-supervised AUC optimization based on positive-unlabeled learning

Machine learning, 2018-04, Vol.107 (4), p.767-794 [Peer Reviewed Journal]

The Author(s) 2017 ;Machine Learning is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-017-5678-9

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15
Learning with tensors: a framework based on convex optimization and spectral regularization
Learning with tensors: a framework based on convex optimization and spectral regularization
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Learning with tensors: a framework based on convex optimization and spectral regularization

Machine learning, 2014-03, Vol.94 (3), p.303-351 [Peer Reviewed Journal]

The Author(s) 2013 ;2015 INIST-CNRS ;The Author(s) 2014 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-013-5366-3

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16
Global optimization based on active preference learning with radial basis functions
Global optimization based on active preference learning with radial basis functions
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Global optimization based on active preference learning with radial basis functions

Machine learning, 2021-02, Vol.110 (2), p.417-448 [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/s10994-020-05935-y

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17
A new large-scale learning algorithm for generalized additive models
A new large-scale learning algorithm for generalized additive models
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A new large-scale learning algorithm for generalized additive models

Machine learning, 2023-09, Vol.112 (9), p.3077-3104 [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/s10994-023-06339-4

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18
Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach
Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach
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Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach

Machine learning, 2020-03, Vol.109 (3), p.643-664 [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/s10994-019-05838-7

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19
Efficient fair principal component analysis
Efficient fair principal component analysis
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Efficient fair principal component analysis

Machine learning, 2022-10, Vol.111 (10), p.3671-3702 [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/s10994-021-06100-9

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20
Optimal control as a graphical model inference problem
Optimal control as a graphical model inference problem
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Optimal control as a graphical model inference problem

Machine learning, 2012-05, Vol.87 (2), p.159-182 [Peer Reviewed Journal]

The Author(s) 2012 ;2015 INIST-CNRS ;info:eu-repo/semantics/openAccess © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/s10994-012-5278-7 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-012-5278-7

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