... Arsany Guirguis, Lê Nguyên Hoang, John Stephan, Geovani Rizk, Sébastien Rouault, and Julien Steiner. They con- tributed to many of the results we present in the manuscript. We would also like to thank other members of our lab who work ...

... Arsany Guirguis, and Sébastien Rouault. Aggregathor: Byzantine machine learn- ing via robust gradient aggregation. In A. Talwalkar, V. Smith, and M. Za- haria, editors, Proceedings of Machine Learning and Systems 2019, vol- ume 1, pages ...

... Guirguis , A ( Guirguis , Arsany ) ; Hoang , LN ( Hoang , Le - Nguyen ) ; Rouault , S ( Rouault , Sebas- tien ) . ( 2022 ) . Genuinely Distributed Byzantine Machine Learning . DISTRIBUTED COMPUTING.Volume 35. Issue 4. Page 305-331 4 ...

For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming".

This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book.

The future of computer networks includes an Internet that encompasses numerous heterogeneous networks, reaches out to the most remote areas, and provides communication in the most extreme and unstable conditions.

Proceedings of the 19th international symposium on computational statistics, held in Paris august 22-27, 2010.Together with 3 keynote talks, there were 14 invited sessions and more than 100 peer-reviewed contributed communications.

This important book provides an up-to-date comprehensive and down-to-earth survey of the theory and practice of extreme value distributions OCo one of the most prominent success stories of modern applied probability and statistics.

This book, edited by four of the leaders of the National Science Foundation’s Global Environment and Network Innovations (GENI) project, gives the reader a tour of the history, architecture, future, and applications of GENI.