暗语 发表于 2025-3-23 11:37:36
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Gabriella Böhmhe shelf by non-experts. To be effective in practice, such systems need to automatically choose a good algorithm and feature preprocessing steps for a new dataset at hand, and also set their respective hyperparameters. Recent work has started to tackle this . problem with the help of efficient BayesAffectation 发表于 2025-3-23 21:37:39
Gabriella Böhmhe shelf by non-experts. To be effective in practice, such systems need to automatically choose a good algorithm and feature preprocessing steps for a new dataset at hand, and also set their respective hyperparameters. Recent work has started to tackle this . problem with the help of efficient Bayes可忽略 发表于 2025-3-24 02:10:22
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Gabriella Böhmted at introductory and intermediate audiencesThis book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciobeisance 发表于 2025-3-24 06:37:58
Gabriella Böhmted at introductory and intermediate audiencesThis book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciinvulnerable 发表于 2025-3-24 12:42:05
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Introduction,s made possible by their common feature of a closed monoidal structure of the category of modules—lifted from different base categories in each case of the discussed Hopf algebra-like structures. In category theoretical terms, liftings of (closed) monoidal structures to module categories correspond核心 发表于 2025-3-24 19:24:54
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(Hopf) Bimonads,m are studied. The general theory of lifting (explained in Chap. .) is applied to the functors and natural transformations constituting the monoidal structure of the base category. A bijection is proven between the liftings of the monoidal structure of the base category to the Eilenberg-Moore catego