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Könyv Machine Learning and Knowledge Discovery in Databases Massih-Reza Amini

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV

Szerző: Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Krali Novak, Grigorios Tsoumakas
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer, Berlin
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
32 741 Ft
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Con...

Információk a könyvről

Szerző
Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Krali Novak, Grigorios Tsoumakas
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2023
oldal
688
EAN
9783031264115
Enbook ID
42806305
Kiadó
Springer, Berlin
Súly
947
Méretek
155 x 235

Teljes leírás

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning;Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

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