815d56cb6e33897dd38ae2ccb33eb4e1 s10207_022_00614_6.pdf 52a721fd892251e34e3fc63714b3a21f74ea6e7c s10207_022_00614_6.pdf 7a4062278081a5fd0a6fa46147bae2f039133c926af1207865cd1107716eb945 s10207_022_00614_6.pdf Title: PSO + FL = PAASO: particle swarm optimization + federated learning = privacy-aware agent swarm optimization Subject: International Journal of Information Security, https://doi.org/10.1007/s10207-022-00614-6 Keywords: Particle swarm optimization; Federated learning; Differential privacy; Masking; Differentially private social choice Author: Vicenç Torra Creator: Springer Producer: Acrobat Distiller 10.1.8 (Windows) CreationDate: Thu Sep 22 07:54:57 2022 CEST ModDate: Mon Oct 10 11:14:55 2022 CEST Tagged: no UserProperties: no Suspects: no Form: AcroForm JavaScript: no Pages: 11 Encrypted: no Page size: 595.276 x 790.866 pts Page rot: 0 File size: 583632 bytes Optimized: yes PDF version: 1.4 name type encoding emb sub uni object ID ------------------------------------ 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s10207_022_00614_6.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2023-07-18 06:12:33 CEST Size: 583632 Format: PDF Version: 1.4 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf Profile: Linearized PDF PDFMetadata: Objects: 419 FreeObjects: 1 IncrementalUpdates: 1 DocumentCatalog: PageLayout: SinglePage PageMode: UseOutlines Language: EN Outlines: Item: Title: PSO + FL = PAASO: particle swarm optimization + federated learning = privacy-aware agent swarm optimization Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4d3167f4 Children: Item: Title: Abstract Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@ed9d034 Item: Title: 1 Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@6121c9d6 Item: Title: 2 Some privacy definitions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@87f383f Children: Item: Title: 2.1 Avoiding disclosure from the computation 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Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@491cc5c9 Item: Title: 4 Experiments and analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@74ad1f1f Children: Item: Title: 4.1 Problems considered Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@6a1aab78 Item: Title: 4.2 Agent (swarm) optimization Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@462d5aee Item: Title: 4.3 Discussion of results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@69b0fd6f Item: Title: 5 Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@757942a1 Children: Item: Title: 5.1 Local and global privacy Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4a87761d Item: Title: 5.2 Future work Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@66d1af89 Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@8646db9 Info: Title: PSO + FL = PAASO: particle swarm optimization + federated learning = privacy-aware agent swarm optimization Author: Vicenç Torra Subject: International Journal of Information Security, https://doi.org/10.1007/s10207-022-00614-6 Keywords: Particle swarm optimization; Federated learning; Differential privacy; Masking; Differentially private social choice Creator: Springer Producer: Acrobat Distiller 10.1.8 (Windows) CreationDate: Thu Sep 22 08:24:57 CEST 2022 ModDate: Mon Oct 10 11:44:55 CEST 2022 ID: 0x1e8368a6c17b7cae37d8d99dd3c662a4, 0xd5c91fd0c18a8c49ab1560d27316a7c8 Filters: FilterPipeline: FlateDecode Fonts: Type1: Font: BaseFont: JHOIEF+MTSYN FontSubset: true FirstChar: 0 LastChar: 255 FontDescriptor: FontName: JHOIEF+MTSYN Flags: Symbolic FontBBox: 0, -954, 1043, 900 FontFile3: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: GDGYRT+CMSY10 FontSubset: true FirstChar: 0 LastChar: 255 FontDescriptor: FontName: GDGYRT+CMSY10 Flags: Nonsymbolic, Italic FontBBox: -29, 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