000			01819nam a2200373Ia 4500
000			03322nam a22003975i 4500
001			978-3-031-28996-5
003			DE-He213
005			20240319120903.0
007			cr nn 008mamaa
008			230328s2023 sz | s |||| 0|eng d
020			_a9783031289965 _9978-3-031-28996-5
082			_a6.3
245			_aTrustworthy Federated Learning _cedited by Randy Goebel, Han Yu, Boi Faltings, Lixin Fan, Zehui Xiong. _h[electronic resource] :
250			_a1st ed. 2023.
260			_aCham _bSpringer International Publishing _c2023
300			_aX, 159 p. 53 illus., 49 illus. in color. _bonline resource.
520			_aThis book constitutes the refereed proceedings of the First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, held in Vienna, Austria, during July 23-25, 2022. The 11 full papers presented in this book were carefully reviewed and selected from 12 submissions. They are organized in three topical sections: answer set programming; adaptive expert models for personalization in federated learning and privacy-preserving federated cross-domain social recommendation.
650			_aApplication software. _931630
650			_aArtificial intelligence. _931631
650			_aArtificial Intelligence. _931632
650			_aComputer and Information Systems Applications. _931633
650			_aComputer Application in Social and Behavioral Sciences. _931634
650			_aData and Information Security. _931635
650			_aData protection. _931636
650			_aSocial sciences _931637
700			_aFaltings, Boi. _931638
700			_aFan, Lixin. _931639
700			_aGoebel, Randy. _931640
700			_aXiong, Zehui. _931641
700			_aYu, Han. _931642
856			_uhttps://doi.org/10.1007/978-3-031-28996-5
942			_cEBK _2ddc
999			_c15231 _d15231