Zobrazeno 1 - 10
of 282
pro vyhledávání: '"Gauthier, François"'
This paper develops a networked federated learning algorithm to solve nonsmooth objective functions. To guarantee the confidentiality of the participants with respect to each other and potential eavesdroppers, we use the zero-concentrated differentia
Externí odkaz:
http://arxiv.org/abs/2306.14012
Autor:
Gauthier, Francois, Gogineni, Vinay Chakravarthi, Werner, Stefan, Huang, Yih-Fang, Kuh, Anthony
Publikováno v:
IEEE Transactions on Signal and Information Processing over Networks (2023) 1-14
This paper presents a personalized graph federated learning (PGFL) framework in which distributedly connected servers and their respective edge devices collaboratively learn device or cluster-specific models while maintaining the privacy of every ind
Externí odkaz:
http://arxiv.org/abs/2306.06399
Autor:
Gauthier, Francois, Gogineni, Vinay Chakravarthi, Werner, Stefan, Huang, Yih-Fang, Kuh, Anthony
Publikováno v:
IEEE Internet of Things Journal (2023)
Online federated learning (FL) enables geographically distributed devices to learn a global shared model from locally available streaming data. Most online FL literature considers a best-case scenario regarding the participating clients and the commu
Externí odkaz:
http://arxiv.org/abs/2303.15226
Autor:
Gauthier, Francois, Bae, Sora
Untrusted deserialization exploits, where a serialised object graph is used to achieve denial-of-service or arbitrary code execution, have become so prominent that they were introduced in the 2017 OWASP Top 10. In this paper, we present a novel and l
Externí odkaz:
http://arxiv.org/abs/2204.09388
Autor:
Gauthier, Francois, Gogineni, Vinay Chakravarthi, Werner, Stefan, Huang, Yih-Fang, Kuh, Anthony
Many assumptions in the federated learning literature present a best-case scenario that can not be satisfied in most real-world applications. An asynchronous setting reflects the realistic environment in which federated learning methods must be able
Externí odkaz:
http://arxiv.org/abs/2111.13931
Autor:
Gauthier, François, Hassanshahi, Behnaz, Selwyn-Smith, Benjamin, Mai, Trong Nhan, Schlüter, Max, Williams, Micah
Following the advent of the American Fuzzy Lop (AFL), fuzzing had a surge in popularity, and modern day fuzzers range from simple blackbox random input generators to complex whitebox concolic frameworks that are capable of deep program introspection.
Externí odkaz:
http://arxiv.org/abs/2108.08455
Over the years, static taint analysis emerged as the analysis of choice to detect some of the most common web application vulnerabilities, such as SQL injection (SQLi) and cross-site scripting (XSS)~\cite{OWASP}. Furthermore, from an implementation p
Externí odkaz:
http://arxiv.org/abs/2103.16240
Autor:
Fronda, Michael P., author, Gauthier, François, author
Publikováno v:
War, Warlords, and Interstate Relations in the Ancient Mediterranean. 28:308-325
