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Machine learning and knowledge discovery in databasesresearch track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings.Part III /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning and knowledge discovery in databasesedited by Danai Koutra ... [et al.].
Reminder of title:	research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings.
remainder title:	ECML PKDD 2023
other author:	Koutra, Danai.
corporate name:
Published:	Cham :Springer Nature Switzerland :2023.
Description:	lv, 707 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Machine learningCongresses.
Online resource:	https://doi.org/10.1007/978-3-031-43418-1
ISBN:	9783031434181$q(electronic bk.)

Machine learning and knowledge discovery in databasesresearch track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings.Part III /
Machine learning and knowledge discovery in databasesresearch track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings.Part III /[electronic resource] :ECML PKDD 2023edited by Danai Koutra ... [et al.]. - Cham :Springer Nature Switzerland :2023. - lv, 707 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,141710302-9743 ;. - Lecture notes in computer science ;4891..

Graph Neural Networks -- Graphs -- Interpretability -- Knowledge Graphs -- Large-scale Learning.

The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment -- Transportation & Urban Planning -- Demo.

ISBN: 9783031434181$q(electronic bk.)

Standard No.: 10.1007/978-3-031-43418-1doiSubjects--Topical Terms:

384498
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning and knowledge discovery in databasesresearch track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings.Part III /
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