000 | 04165nam a22006495i 4500 | ||
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001 | 978-3-031-28996-5 | ||
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008 | 230328s2023 sz | s |||| 0|eng d | ||
020 |
_a9783031289965 _9978-3-031-28996-5 |
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_aTrustworthy Federated Learning _h[electronic resource] : _bFirst International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers / _cedited by Randy Goebel, Han Yu, Boi Faltings, Lixin Fan, Zehui Xiong. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
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300 |
_aX, 159 p. 53 illus., 49 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
||
490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v13448 |
|
500 | _aAcceso multiusuario | ||
505 | 0 | _aAdaptive Expert Models for Personalization in Federated Learning -- Federated Learning with GAN-based Data Synthesis for Non-iid Clients -- Practical and Secure Federated Recommendation with Personalized Mask -- A General Theory for Client Sampling in Federated Learning -- Decentralized adaptive clustering of deep nets is beneficial for client collaboration -- Sketch to Skip and Select: Communication Efficient Federated Learning using Locality Sensitive Hashing -- Fast Server Learning Rate Tuning for Coded Federated Dropout -- FedAUXfdp: Differentially Private One-Shot Federated Distillation -- Secure forward aggregation for vertical federated neural network -- Two-phased Federated Learning with Clustering and Personalization for Natural Gas Load Forecasting -- Privacy-Preserving Federated Cross-Domain Social Recommendation. | |
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. | ||
541 |
_fUABC ; _cPerpetuidad |
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650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aData protection. | |
650 | 0 |
_aSocial sciences _xData processing. |
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650 | 0 | _aApplication software. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aData and Information Security. |
650 | 2 | 4 | _aComputer Application in Social and Behavioral Sciences. |
650 | 2 | 4 | _aComputer and Information Systems Applications. |
700 | 1 |
_aGoebel, Randy. _eeditor. _0(orcid)0000-0002-0739-2946 _1https://orcid.org/0000-0002-0739-2946 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aYu, Han. _eeditor. _0(orcid)0000-0001-6893-8650 _1https://orcid.org/0000-0001-6893-8650 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aFaltings, Boi. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aFan, Lixin. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aXiong, Zehui. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031289958 |
776 | 0 | 8 |
_iPrinted edition: _z9783031289972 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v13448 |
|
856 | 4 | 0 |
_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-28996-5 |
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