Works matching IS 08856125 AND DT 2023 AND VI 112 AND IP 9
Results: 15
Robust estimation in regression and classification methods for large dimensional data.
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- Machine Learning, 2023, v. 112, n. 9, p. 3361, doi. 10.1007/s10994-023-06349-2
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NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation.
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- Machine Learning, 2023, v. 112, n. 9, p. 3473, doi. 10.1007/s10994-023-06343-8
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FairSwiRL: fair semi-supervised classification with representation learning.
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- Machine Learning, 2023, v. 112, n. 9, p. 3051, doi. 10.1007/s10994-023-06342-9
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A3T: accuracy aware adversarial training.
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- Machine Learning, 2023, v. 112, n. 9, p. 3191, doi. 10.1007/s10994-023-06341-w
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A new large-scale learning algorithm for generalized additive models.
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- Machine Learning, 2023, v. 112, n. 9, p. 3077, doi. 10.1007/s10994-023-06339-4
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The role of mutual information in variational classifiers.
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- Machine Learning, 2023, v. 112, n. 9, p. 3105, doi. 10.1007/s10994-023-06337-6
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Classifier calibration: a survey on how to assess and improve predicted class probabilities.
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- Machine Learning, 2023, v. 112, n. 9, p. 3211, doi. 10.1007/s10994-023-06336-7
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Considerations when learning additive explanations for black-box models.
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- Machine Learning, 2023, v. 112, n. 9, p. 3333, doi. 10.1007/s10994-023-06335-8
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Learning system parameters from turing patterns.
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- Machine Learning, 2023, v. 112, n. 9, p. 3151, doi. 10.1007/s10994-023-06334-9
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Contrastive counterfactual visual explanations with overdetermination.
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- Machine Learning, 2023, v. 112, n. 9, p. 3497, doi. 10.1007/s10994-023-06333-w
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Ensemble and continual federated learning for classification tasks.
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- Machine Learning, 2023, v. 112, n. 9, p. 3413, doi. 10.1007/s10994-023-06330-z
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Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification.
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- Machine Learning, 2023, v. 112, n. 9, p. 3455, doi. 10.1007/s10994-023-06327-8
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ROAD-R: the autonomous driving dataset with logical requirements.
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- Machine Learning, 2023, v. 112, n. 9, p. 3261, doi. 10.1007/s10994-023-06322-z
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Faster Riemannian Newton-type optimization by subsampling and cubic regularization.
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- Machine Learning, 2023, v. 112, n. 9, p. 3527, doi. 10.1007/s10994-023-06321-0
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Refining neural network predictions using background knowledge.
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- Machine Learning, 2023, v. 112, n. 9, p. 3293, doi. 10.1007/s10994-023-06310-3
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