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000890933 019__ $$a1105190489
000890933 020__ $$a9783030199456$$q(electronic book)
000890933 020__ $$a3030199452$$q(electronic book)
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000890933 0247_ $$a10.1007/978-3-030-19945-6$$2doi
000890933 0247_ $$a10.1007/978-3-030-19
000890933 035__ $$aSP(OCoLC)on1104357896
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000890933 1112_ $$aMLN (Conference)$$n(1st :$$d2018 :$$cParis, France)
000890933 24510 $$aMachine learning for networking :$$bfirst International Conference, MLN 2018, Paris, France, November 27-29, 2018, Revised selected papers /$$cÉric Renault, Paul Mühlethaler, Selma Boumerdassi (eds.).
000890933 2463_ $$aMLN 2018
000890933 264_1 $$aCham, Switzerland :$$bSpringer,$$c2019.
000890933 300__ $$a1 online resource (xiii, 388 pages) :$$billustrations.
000890933 336__ $$atext$$btxt$$2rdacontent
000890933 337__ $$acomputer$$bc$$2rdamedia
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000890933 4901_ $$aLecture notes in computer science ;$$v11407
000890933 4901_ $$aLNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
000890933 500__ $$aIncludes author index.
000890933 5050_ $$aLearning Concave-Convex Profiles of Data Transport Over Dedicated Connections -- Towards Analyzing C-ITS Security Data -- Towards a Statistical Approach for User Classification in Twitter -- RILNET: A Reinforcement Learning Based Load Balancing Approach for Datacenter Networks -- Building a Wide-Area File Transfer Performance Predictor: An Empirical Study -- Advanced Hybrid Technique in Detecting Cloud Web Application's Attacks -- Machine-Learned Classifiers for Protocol Selection on a Shared Network -- Common Structures in Resource Management as Driver for Reinforcement Learning: a Survey and Research Tracks -- Inverse Kinematics Using Arduino and Unity for People with Motor Skill Limitations -- Delmu: A Deep Learning Approach to Maximizing the Utility of Virtualised Millimetre-Wave Backhauls -- Malware Detection System Based on an In-depth Analysis of the Portable Executable Headers -- DNS Traffic Forecasting Using Deep Neural Networks -- Energy-Based Connected Dominating Set for Data Aggregation for Intelligent Wireless Sensor Networks -- Touchless Recognition of Hand Gesture Digits and English Characters Using Convolutional Neural Networks -- LSTM Recurrent Neural Network for Anomaly Detection in Cellular Mobile Networks -- Towards a Better Compromise Between Shallow and Deep CNN for Binary Classification Problems of Unstructured Data -- Reinforcement Learning Based Routing Protocols Analysis for Mobile Ad-Hoc Networks -- Deep Neural Ranking for Crowdsourced Geopolitical Event Forecasting -- The Comment of BBS: How Investor Sentiment Affects a Share Market of China -- A Hybrid Neural Network Approach for Lung Cancer Classification with Gene Expression Dataset and Prior Biological Knowledge -- Plant Leaf Disease Detection and Classification Using Particle Swarm Optimization -- A Game Theory Approach for Intrusion Prevention Systems -- WSN Heterogeneous Architecture Platform for IoT -- An IoT Framework for Detecting Movement Within Indoor Environments -- A Hybrid Architecture for Cooperative UAV and USV Swarm Vehicles -- Detecting Suspicious Transactions in Smart Living Spaces -- Intelligent ERP Based Multi Agent Systems and Cloud Computing.
000890933 506__ $$aAccess limited to authorized users.
000890933 520__ $$aThis book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
000890933 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 13, 2019).
000890933 650_0 $$aMachine learning$$vCongresses.
000890933 7001_ $$aRenault, Éric,$$eeditor.
000890933 7001_ $$aMühlethaler, Paul,$$eeditor.
000890933 7001_ $$aBoumerdassi, Selma,$$eeditor.
000890933 830_0 $$aLecture notes in computer science ;$$v11407.
000890933 830_0 $$aLNCS sublibrary.$$nSL 3,$$pInformation systems and applications, incl. Internet/Web, and HCI.
000890933 852__ $$bebk
000890933 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-19945-6$$zOnline Access$$91397441.1
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