ECML PKDD 2018 Workshops = Nemesis 2...
ECML PKDD (Conference) (2018 :)

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  • ECML PKDD 2018 Workshops = Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018 : proceedings /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: ECML PKDD 2018 Workshops/ edited by Carlos Alzate ... [et al.].
    其他題名: Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018 : proceedings /
    其他題名: ECML PKDD 2018
    其他作者: Alzate, Carlos.
    團體作者: ECML PKDD (Conference)
    出版者: Cham :Springer International Publishing : : 2019.,
    面頁冊數: x, 257 p. :ill., digital ;24 cm.
    內容註: Label Sanitization against Label Flipping Poisoning Attacks -- Limitations of the Lipschitz constant as a Defense Against Adversarial Examples -- Understanding Adversarial Space through the Lens of Attribution -- Detecting Potential Local Adversarial Examples for Human-Interpretable Defense -- Smart Cities with Deep Edges -- Computational Model for Urban Growth Using Socioeconomic Latent Parameters -- Object Geolocation from Crowdsourced Street Level Imagery -- Extending Support Vector Regression to Constraint Optimization: Application to the Reduction of Potentially Avoidable Hospitalizations -- SALER: a Data Science Solution to Detect and Prevent Corruption in Public Administration -- MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities -- Designing Data-Driven Solutions to Societal Problems: Challenges and Approaches -- Host based Intrusion Detection System with Combined CNN/RNN Model -- Cyber Attacks against the PC Learning Algorithm -- Neural Networks in an Adversarial Setting and Ill-Conditioned Weight Space -- Pseudo-Random Number Generation using Generative Adversarial Networks -- Context Delegation for Context-Based Access Control -- An Information Retrieval System For CBRNe Incidents -- A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support -- Event relevancy pruning in support of energy-efficient sequential pattern mining -- How to Measure Energy Consumption in Machine Learning Algorithms.
    Contained By: Springer eBooks
    標題: Machine learning - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-030-13453-2
    ISBN: 9783030134532
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