Works matching IS 08856125 AND DT 2023 AND VI 112 AND IP 1
Results: 11
Limits of multi-relational graphs.
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- Machine Learning, 2023, v. 112, n. 1, p. 177, doi. 10.1007/s10994-022-06281-x
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A family of pairwise multi-marginal optimal transports that define a generalized metric.
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- Machine Learning, 2023, v. 112, n. 1, p. 353, doi. 10.1007/s10994-022-06280-y
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Reconciling privacy and utility: an unscented Kalman filter-based framework for differentially private machine learning.
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- Machine Learning, 2023, v. 112, n. 1, p. 311, doi. 10.1007/s10994-022-06279-5
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Dynamic customer segmentation via hierarchical fragmentation-coagulation processes.
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- Machine Learning, 2023, v. 112, n. 1, p. 281, doi. 10.1007/s10994-022-06276-8
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MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm.
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- Machine Learning, 2023, v. 112, n. 1, p. 99, doi. 10.1007/s10994-022-06275-9
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Multi-armed bandits with censored consumption of resources.
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- Machine Learning, 2023, v. 112, n. 1, p. 217, doi. 10.1007/s10994-022-06271-z
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Online learning of network bottlenecks via minimax paths.
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- Machine Learning, 2023, v. 112, n. 1, p. 131, doi. 10.1007/s10994-022-06270-0
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Generalizing p-Laplacian: spectral hypergraph theory and a partitioning algorithm.
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- Machine Learning, 2023, v. 112, n. 1, p. 241, doi. 10.1007/s10994-022-06264-y
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SLISEMAP: supervised dimensionality reduction through local explanations.
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- Machine Learning, 2023, v. 112, n. 1, p. 1, doi. 10.1007/s10994-022-06261-1
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Root-finding approaches for computing conformal prediction set.
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- Machine Learning, 2023, v. 112, n. 1, p. 151, doi. 10.1007/s10994-022-06233-5
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Partially Hidden Markov Chain Multivariate Linear Autoregressive model: inference and forecasting—application to machine health prognostics.
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- Machine Learning, 2023, v. 112, n. 1, p. 45, doi. 10.1007/s10994-022-06209-5
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- Article