Federated learning (FL) has emerged as a key technique for distributed
m...
Semi-decentralized federated learning blends the conventional device
to-...
Federated learning (FL) has been promoted as a popular technique for tra...
Symbol detection is a fundamental and challenging problem in modern
comm...
Federated learning (FL) has been recognized as one of the most promising...
We propose cooperative edge-assisted dynamic federated learning (CE-FL)....
Federated learning is a prime candidate for distributed machine learning...
Federated learning (FedL) has emerged as a popular technique for distrib...
Error correcting codes are a fundamental component in modern day
communi...
Edge computing has revolutionized the world of mobile and wireless netwo...
We consider distributed machine learning (ML) through unmanned aerial
ve...
We focus on the use of proxy distributions, i.e., approximations of the
...
We ask the following question: what training information is required to
...
The conventional federated learning (FedL) architecture distributes mach...
In recent years, edge computing has become a popular choice for
latency-...
Evaluation of adversarial robustness is often error-prone leading to
ove...
We study the effects of allowing paid prioritization arrangements in a m...
Federated learning has emerged recently as a promising solution for
dist...
With increasing expressive power, deep neural networks have significantl...
Contemporary network architectures are pushing computing tasks from the ...
Attacks on Internet routing are typically viewed through the lens of
ava...
Cyberphysical systems (CPS) are ubiquitous in our personal and professio...
Storage has become a constrained resource on smartphones. Gaming is a po...
A large body of recent work has investigated the phenomenon of evasion
a...
Fog computing, which distributes computing resources to multiple locatio...
Social learning, i.e., students learning from each other through social
...
The Rasch model is widely used for item response analysis in application...
Sign recognition is an integral part of autonomous cars. Any
misclassifi...
Co-flows model a modern scheduling setting that is commonly found in a
v...
Probit regression was first proposed by Bliss in 1934 to study mortality...
We propose a new real-world attack against the computer vision based sys...
Many recent proposals for anonymous communication omit from their securi...
Among storage components, hard disk drives (HDDs) have become the most
c...
This paper introduces an analytical framework to investigate optimal des...