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Engineering resilient collective adaptive systems by self-stabilisation
Viroli M., Audrito G., Beal J., Damiani F., Pianini D. ACM Transactions on Modeling and Computer Simulation 28(2): 1-28, 2018. Type: Article
Smart cities, together with the Internet of Things (IoT), are becoming reality at an accelerated speed, supported by the fifth generation of mobile technology (5G) and other advances in technology. The supporting networked computational systems in...
Jul 13 2020
Trustworthy cyber-physical systems: a systematic framework towards design and evaluation of trust and trustworthiness
Nazila G., Springer International Publishing, New York, NY, 2019. 344 pp. Type: Book (978-3-658274-87-0)
Users expect a trustworthy system to behave according to its requirements. Trustworthiness is a fundamental design objective for any system that provides critical functions, for example, transportation systems, medical systems, and water purificat...
Jul 6 2020
Multiplatform MOOC analytics: comparing global and regional patterns in edX and Edraak
Ruipérez-Valiente J., Halawa S., Reich J. L@S 2019 (Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale, Chicago, IL, Jun 24-25, 2019) 1-9, 2019. Type: Proceedings
Outcomes from a regional massive open online course (MOOC) are better than those from a global MOOC. The best-known MOOCs are global, such as edX, Coursera, and FutureLearn, but regional MOOCs exist. The paper compares the effectiveness of an Arab...
Jun 29 2020
Improving fairness in machine learning systems: what do industry practitioners need?
Holstein K., Wortman Vaughan J., Hal I., Dudik M., Wallach H. CHI 2019 (Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, UK, May 4-9, 2019) 1-16, 2019. Type: Proceedings
Research works involving qualitative methods are generally rare in technical domains. Holstein et al. break this trend, however, as they set out to explore fairness in machine learning systems, deploying empirical methods to arrive at conclusions....
Jun 22 2020
Formal methods: an appetizer
Nielson F., Nielson H., Springer International Publishing, New York, NY, 2019. 162 pp. Type: Book (978-3-030051-55-6)
I’ve occasionally been intimidated into ordering an appetizer as the main course, but have rarely regretted it thanks to the presence of “gourmet” friends. This is an excellent, ultra-elegant, and rigorous book. Its 160 printed p...
Jun 15 2020
Discrete geodesic nets for modeling developable surfaces
Rabinovich M., Hoffmann T., Sorkine-Hornung O. ACM Transactions on Graphics 37(2): 1-17, 2018. Type: Article
Developable surfaces are those that can be flattened to the plane isometrically, that is, without stretching or tearing. They play an important role in manufacturing and architecture, for example, curved glass can be constructed by rolling and ben...
Jun 8 2020
Introduction to distributed self-stabilizing algorithms
Altisen K., Devismes S., Dubois S., Petit F., Morgan&Claypool Publishers, San Rafael, CA, 2019. 166 pp. Type: Book (978-1-681735-36-8)
Distribution is one of the most pervasive features of modern computing architectures. From the multiple specialized processors that make up a personal computer, to the network of computers in a modern automobile, to the Internet itself, modern sys...
Jun 1 2020
Fairness-aware machine learning: practical challenges and lessons learned
Bird S., Hutchinson B., Kenthapadi K., K c man E., Mitchell M. WWW 2019 (Companion Proceedings of The 2019 World Wide Web Conference, San Francisco, CA, May 13-17, 2019) 1297-1298, 2019. Type: Proceedings
This is a timely paper in light of recent stories about bias in artificial intelligence (AI) systems, such as the COMPAS system used in Florida to predict recidivism. The tutorial’s aim is to describe what the authors call a “fairness-...
May 26 2020
Cross-lingual word embeddings
Søgaard A., Faruqui M., Vulić I., Ruder S., Morgan&Claypool Publishers, San Rafael, CA, 2019. 134 pp. Type: Book (978-1-681730-63-9)
From the back cover:...
May 18 2020
Rebooting AI: building artificial intelligence we can trust
Marcus G., Davis E., Pantheon Books, New York, NY, 2019. 288 pp. Type: Book (978-1-524748-25-8)
A fast and light read, yet nonetheless important, this book proposes that artificial intelligence (AI) will eventually achieve many, or even all, of the goals promised by developers and the press. But the authors maintain that this will not be ach...
May 11 2020
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