000 04335nam a22006735i 4500
001 978-3-031-43412-9
003 DE-He213
005 20240730200639.0
007 cr nn 008mamaa
008 230916s2023 sz | s |||| 0|eng d
020 _a9783031434129
_9978-3-031-43412-9
024 7 _a10.1007/978-3-031-43412-9
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aMachine Learning and Knowledge Discovery in Databases: Research Track
_h[electronic resource] :
_bEuropean Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part I /
_cedited by Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aLV, 761 p. 203 illus., 191 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14169
505 0 _aActive Learning -- Adversarial Machine Learning -- Anomaly Detection -- Applications -- Bayesian Methods -- Causality -- Clustering.
520 _aThe 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.
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer engineering.
_910164
650 0 _aComputer networks .
_931572
650 0 _aComputers.
_98172
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_9164239
650 0 _aSoftware engineering.
_94138
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Engineering and Networks.
_9164240
650 2 4 _aComputing Milieux.
_955441
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aSoftware Engineering.
_94138
700 1 _aKoutra, Danai.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9164241
700 1 _aPlant, Claudia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9164242
700 1 _aGomez Rodriguez, Manuel.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9164243
700 1 _aBaralis, Elena.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9164244
700 1 _aBonchi, Francesco.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9164245
710 2 _aSpringerLink (Online service)
_9164246
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031434112
776 0 8 _iPrinted edition:
_z9783031434136
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14169
_9164247
856 4 0 _uhttps://doi.org/10.1007/978-3-031-43412-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c96159
_d96159