Lifting symmetry breaking constraints with inductive logic programming.
- Published in:
- Machine Learning, 2022, v. 111, n. 4, p. 1303, doi. 10.1007/s10994-022-06146-3
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- Publication type:
- Article
Works matching IS 08856125 AND DT 2022 AND VI 111 AND IP 4
Results: 12
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SDANet: spatial deep attention-based for point cloud classification and segmentation.
- Published in:
- Machine Learning, 2022, v. 111, n. 4, p. 1327, doi. 10.1007/s10994-022-06148-1
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- Article
3
Efficient SVDD sampling with approximation guarantees for the decision boundary.
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- Machine Learning, 2022, v. 111, n. 4, p. 1349, doi. 10.1007/s10994-022-06149-0
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- Publication type:
- Article
4
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning.
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- Machine Learning, 2022, v. 111, n. 4, p. 1431, doi. 10.1007/s10994-022-06144-5
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- Publication type:
- Article
5
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework.
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- Machine Learning, 2022, v. 111, n. 4, p. 1523, doi. 10.1007/s10994-022-06142-7
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- Publication type:
- Article
6
Few-shot learning for spatial regression via neural embedding-based Gaussian processes.
- Published in:
- Machine Learning, 2022, v. 111, n. 4, p. 1239, doi. 10.1007/s10994-021-06118-z
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- Publication type:
- Article
7
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning.
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- Machine Learning, 2022, v. 111, n. 4, p. 1551, doi. 10.1007/s10994-021-06109-0
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- Article
8
Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks.
- Published in:
- Machine Learning, 2022, v. 111, n. 4, p. 1377, doi. 10.1007/s10994-022-06129-4
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- Publication type:
- Article
9
Time-aware tensor decomposition for sparse tensors.
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- Machine Learning, 2022, v. 111, n. 4, p. 1409, doi. 10.1007/s10994-021-06059-7
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- Article
10
Polynomial-based graph convolutional neural networks for graph classification.
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- Machine Learning, 2022, v. 111, n. 4, p. 1205, doi. 10.1007/s10994-021-06098-0
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- Publication type:
- Article
11
Handling epistemic and aleatory uncertainties in probabilistic circuits.
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- Machine Learning, 2022, v. 111, n. 4, p. 1259, doi. 10.1007/s10994-021-06086-4
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- Publication type:
- Article
12
Improving sequential latent variable models with autoregressive flows.
- Published in:
- Machine Learning, 2022, v. 111, n. 4, p. 1597, doi. 10.1007/s10994-021-06092-6
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- Publication type:
- Article