Nirupam Gupta – författare
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5 produkter
Networked Systems
12th International Conference, NETYS 2024, Rabat, Morocco, May 29–31, 2024, Proceedings
Av Armando Castañeda, Constantin Enea m. fl.
Häftad, 2024
737 kr
Lägg i varukorg
This book constitutes the refereed proceedings of the 12th International Conference on Networked Systems, NETYS 2024, held in Rabat, Morocco, during May 29-31, 2024.The 14 full papers and 3 short papers presented were carefully reviewed and selected from 42 submissions. NETYS aims to bring together …
Networked Systems
12th International Conference, NETYS 2024, Rabat, Morocco, May 29–31, 2024, Proceedings
Av Nirupam Gupta, Constantin Enea m. fl.
E-bok, 2024
923 kr
Lägg i varukorg
This book constitutes the refereed proceedings of the 12th International Conference on Networked Systems, NETYS 2024, held in Rabat, Morocco, during May 29-31, 2024. The 14 full papers and 3 short papers presented were carefully reviewed and selected from 42 submissions. NETYS aims to bring …
Robust Machine Learning
Distributed Methods for Safe AI
Av Rachid Guerraoui, Nirupam Gupta m. fl.
Inbunden, 2024
1580 kr
Lägg i varukorg
Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning …
Robust Machine Learning
Distributed Methods for Safe AI
Av Rafael Pinot, Nirupam Gupta m. fl.
E-bok, 2024
2006 kr
Lägg i varukorg
Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning …
Robust Machine Learning
Distributed Methods for Safe AI
Av Rachid Guerraoui, Nirupam Gupta m. fl.
Häftad, 2025
1580 kr
Lägg i varukorg
Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning …
