Narrow your search

Library

KU Leuven (2)

Odisee (2)

Thomas More Kempen (2)

Thomas More Mechelen (2)

UCLL (2)

UGent (2)

ULB (2)

ULiège (2)

VIVES (2)

KBC (1)


Resource type

book (2)


Language

English (2)


Year
From To Submit

2021 (1)

2020 (1)

Listing 1 - 2 of 2
Sort by

Book
Heterogeneous data management, polystores, and analytics for healthcare : vldb workshops, poly 2020 and dmah 2020, virtual event, august 31 and september 4, 2020, revised selected papers
Author:
ISBN: 3030710556 3030710548 Year: 2021 Publisher: Cham, Switzerland : Springer,

Loading...
Export citation

Choose an application

Bookmark

Abstract

This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020, which were held virtually on August 31 and September 4, 2020. For Poly 2020, 4 full and 3 short papers were accepted from 10 submissions; and for DMAH 2020, 7 full and 2 short papers were accepted from a total of 15 submissions. The papers were organized in topical sections as follows: Privacy, Security and/or Policy Issues for Heterogenous Data; COVID-19 Data Analytics and Visualization; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.


Book
Federated learning : privacy and incentive
Authors: --- ---
ISBN: 3030630765 3030630757 Year: 2020 Publisher: Cham, Switzerland : Springer,

Loading...
Export citation

Choose an application

Bookmark

Abstract

This book provides a comprehensive and self-contained introduction to Federated Learning, ranging from the basic knowledge and theories to various key applications, and the privacy and incentive factors are the focus of the whole book. This book is timely needed since Federated Learning is getting popular after the release of the General Data Protection Regulation (GDPR). As Federated Learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. First, it introduces different privacy-preserving methods for protecting a Federated Learning model against different types of attacks such as Data Leakage and/or Data Poisoning. Second, the book presents incentive mechanisms which aim to encourage individuals to participate in the Federated Learning ecosystems. Last but not the least, this book also describes how Federated Learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both academia and industries, who would like to learn federated learning from scratch, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing are preferred.

Keywords

Artificial intelligence. --- Computer security. --- Computer communication systems. --- Application software. --- Artificial Intelligence. --- Systems and Data Security. --- Computer Communication Networks. --- Computer Applications. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Protection of computer systems --- Security of computer systems --- Data protection --- Security systems --- Hacking --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Distributed processing --- Protection --- Security measures --- Federated database systems. --- Machine learning. --- Learning, Machine --- Artificial intelligence --- Database systems, Federated --- FDBSs (Federated database systems) --- Federated systems (Database management) --- Systems, Federated (Database management) --- Metadatabases --- Management

Listing 1 - 2 of 2
Sort by