LEADER 00892nam0-2200301 --450 001 9910579701303321 005 20240524175729.0 010 $a978-88-8402-660-6 020 $aIT$b2009-5670 100 $a20220708d2009----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $ay 001yy 200 1 $a<>Perticari confutato da Dante$fNiccolò Tommaseo$ga cura di Luisanna Tremonti 210 $aRoma$cSalerno$d2009 215 $aLVIII, 170 p.$d23 cm 225 1 $aTesti e documenti di letteratura e di lingua$v30 610 0 $aQuestione della lingua 620 $aIT$dRoma 700 1$aTommaseo,$bNiccolò$0337187 702 1$aTremonti,$bLuisanna 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910579701303321 952 $a808.8 TEDLL 30$b2022/940$fFLFBC 959 $aFLFBC 996 $aPerticari confutato da Dante$9251103 997 $aUNINA LEADER 03689nam 22006015 450 001 996691670603316 005 20251013130441.0 010 $a3-032-00552-3 024 7 $a10.1007/978-3-032-00552-6 035 $a(MiAaPQ)EBC32344483 035 $a(Au-PeEL)EBL32344483 035 $a(CKB)41633856700041 035 $a(DE-He213)978-3-032-00552-6 035 $a(OCoLC)1545646001 035 $a(EXLCZ)9941633856700041 100 $a20251013d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning for Networking $e7th International Conference, MLN 2024, Reims, France, November 27?29, 2024, Revised Selected Papers /$fedited by Fouchal Hacène, Boumerdassi Selma, Renault Éric 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (286 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15540 311 08$a3-032-00551-5 327 $a -- Learning per-flow SD-WAN load-balancing policies. -- Survey on Federated Learning in Smart Healthcare. -- Complex Communication Networks Management with Distributed AI:Challenges and Open Issues. -- A Framework for Global Trust and Reputation Management in 6G Networks. -- DRL Framework for Minimizing Beam Switching Time and Maintaining QoS in 6G-V2X Base Stations. -- Reducing BLE energy loss in busy 2.4GHz band. -- Leveraging SHAP to advance the Robustness of Large Language Models. -- Keyword-Driven Email Classification: Leveraging Machine Learning Techniques. -- Predicting Intents: ARMA-Based Modeling. -- Design and Evaluation of a Lightweight SDN Controller for Integrated Road and Rail Networks. -- PiPS: An effective strategy and approach for Privacy in Public Surveillance. -- A comprehensive review of deep learning approaches for tomato leaf diseases detection and classification in smart agriculture. -- A review on advancement in PEM Fuel cell Diagnosis based on Machine learning techniques. -- GPS Spoofing Attack against UAVs: a timeseries dataset case study. 330 $aThis book constitutes the refereed proceedings of the 7th International Conference on Machine Learning for Networking, MLN 2024, held in Reims, France, during November 27?29, 2024. The 14 full papers presented in this book were carefully reviewed and selected from 25 submissions. The International Conference on Machine Learning for Networking (MLN) aims at providing a top forum for researchers and practitioners to present and discuss new trends in machine learning, deep learning, pattern recognition and optimization for network architectures and service. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15540 606 $aData mining 606 $aComputer networks 606 $aApplication software 606 $aData Mining and Knowledge Discovery 606 $aComputer Communication Networks 606 $aComputer and Information Systems Applications 615 0$aData mining. 615 0$aComputer networks. 615 0$aApplication software. 615 14$aData Mining and Knowledge Discovery. 615 24$aComputer Communication Networks. 615 24$aComputer and Information Systems Applications. 676 $a006.312 700 $aHacène$b Fouchal$01860706 701 $aSelma$b Boumerdassi$01860707 701 $aÉric$b Renault$0128132 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996691670603316 996 $aMachine Learning for Networking$94466454 997 $aUNISA