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Titlebook: Advances in Intelligent Data Analysis XIX; 19th International S Pedro Henriques Abreu,Pedro Pereira Rodrigues,Jo?o Conference proceedings 2

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21#
發(fā)表于 2025-3-25 03:31:30 | 只看該作者
978-3-030-74250-8Springer Nature Switzerland AG 2021
22#
發(fā)表于 2025-3-25 10:23:43 | 只看該作者
0302-9743 place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021..The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling
23#
發(fā)表于 2025-3-25 12:20:31 | 只看該作者
24#
發(fā)表于 2025-3-25 17:27:54 | 只看該作者
25#
發(fā)表于 2025-3-25 22:49:58 | 只看該作者
https://doi.org/10.1007/978-3-319-55708-3onent to the loss function that penalises non-monotonic gradients. Our method is evaluated on classification and regression tasks using two datasets. Our model is able to conform to known monotonic relations, improving trustworthiness in decision making, while simultaneously maintaining small and controllable degradation in predictive ability.
26#
發(fā)表于 2025-3-26 00:51:51 | 只看該作者
27#
發(fā)表于 2025-3-26 07:34:27 | 只看該作者
28#
發(fā)表于 2025-3-26 11:43:57 | 只看該作者
Antonella Costanzo,Domenico Vistoccoity. We evaluate our approach for image classification using Convolutional NNs. We show that reconstructed visualizations using encodings from a classifier capture more relevant information for classification than conventional AEs. Relevant code is available at ..
29#
發(fā)表于 2025-3-26 13:25:30 | 只看該作者
Conference proceedings 2021ly reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats. .
30#
發(fā)表于 2025-3-26 18:24:56 | 只看該作者
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