Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods.
- Published in:
- Machine Learning, 2021, v. 110, n. 3, p. 457, doi. 10.1007/s10994-021-05946-3
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- Publication type:
- Article
Works matching IS 08856125 AND DT 2021 AND VI 110 AND IP 3
Results: 6
1
2
F*: an interpretable transformation of the F-measure.
- Published in:
- Machine Learning, 2021, v. 110, n. 3, p. 451, doi. 10.1007/s10994-021-05964-1
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- Publication type:
- Article
3
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach.
- Published in:
- 2021
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- Publication type:
- Correction Notice
4
Coupling matrix manifolds assisted optimization for optimal transport problems.
- Published in:
- Machine Learning, 2021, v. 110, n. 3, p. 533, doi. 10.1007/s10994-020-05931-2
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- Publication type:
- Article
5
Reshaped tensor nuclear norms for higher order tensor completion.
- Published in:
- Machine Learning, 2021, v. 110, n. 3, p. 507, doi. 10.1007/s10994-020-05927-y
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- Publication type:
- Article
6
Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling.
- Published in:
- Machine Learning, 2021, v. 110, n. 3, p. 559, doi. 10.1007/s10994-020-05912-5
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- Publication type:
- Article