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Titlebook: Scalable Uncertainty Management; 14th International C Jesse Davis,Karim Tabia Conference proceedings 2020 Springer Nature Switzerland AG 20

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樓主: Animosity
41#
發(fā)表于 2025-3-28 16:04:41 | 只看該作者
42#
發(fā)表于 2025-3-28 21:59:03 | 只看該作者
43#
發(fā)表于 2025-3-28 23:51:35 | 只看該作者
44#
發(fā)表于 2025-3-29 06:36:05 | 只看該作者
Inference with Choice Functions Made?Practicalhenever possible, and use this natural extension to make new choices. We present a practical algorithm to compute this natural extension and provide several methods that can be used to improve its scalability.
45#
發(fā)表于 2025-3-29 07:50:35 | 只看該作者
A Formal Learning Theory for Three-Way Clusteringtional hard clustering one, we provide a constructive proof of an existence theorem, that is, we show an algorithm which satisfies the proposed axioms. We also propose an axiomatic characterization of the three-way k-means algorithm family and draw comparisons between the two approaches.
46#
發(fā)表于 2025-3-29 13:23:57 | 只看該作者
47#
發(fā)表于 2025-3-29 15:59:25 | 只看該作者
48#
發(fā)表于 2025-3-29 23:17:43 | 只看該作者
49#
發(fā)表于 2025-3-30 02:10:52 | 只看該作者
Score-Based Explanations in Data Management and Machine Learningrom classification models. The described approaches are mostly of a causal and counterfactual nature. We argue for the need to bring domain and semantic knowledge into score computations; and suggest some ways to do this.
50#
發(fā)表于 2025-3-30 06:54:11 | 只看該作者
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