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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 de Carlos Alzate

ECML PKDD 2018 Workshops: Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings: Lecture Notes in Computer Science, cartea 11329

Editat de Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
en Limba Engleză Paperback – 16 feb 2019
This book constitutes revised selected papers from the workshops Nemesis, UrbReas, SoGood, IWAISe, and Green Data Mining, held at the 18th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018.
 
The 20 papers presented in this volume were carefully reviewed and selected from a total of 32 submissions. The workshops included are:
Nemesis 2018: First Workshop on Recent Advances in Adversarial Machine Learning UrbReas 2018: First International Workshop on Urban Reasoning from Complex Challenges in Cities
SoGood 2018: Third Workshop on Data Science for Social Good IWAISe 2018: Second International Workshop on Artificial Intelligence in Security
Green Data Mining 2018: First International Workshop on Energy Efficient Data Mining and Knowledge Discovery
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Specificații

ISBN-13: 9783030134525
ISBN-10: 3030134520
Pagini: 244
Ilustrații: X, 257 p. 92 illus., 59 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.39 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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 AdversarialSetting 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.