Federated learning with differential privacy: Algorithms and performance analysis
Federated learning (FL), as a type of distributed machine learning, is capable of significantly
preserving clients' private data from being exposed to adversaries. Nevertheless, private …
preserving clients' private data from being exposed to adversaries. Nevertheless, private …
Scheduling policies for federated learning in wireless networks
Motivated by the increasing computational capacity of wireless user equipments (UEs), eg,
smart phones, tablets, or vehicles, as well as the increasing concerns about sharing private …
smart phones, tablets, or vehicles, as well as the increasing concerns about sharing private …
Allelic variation in gene expression is common in the human genome
HS Lo, Z Wang, Y Hu, HH Yang, S Gere… - Genome …, 2003 - genome.cshlp.org
Variations in gene sequence and expression underlie much of human variability. Despite
the known biological roles of differential allelic gene expression resulting from X …
the known biological roles of differential allelic gene expression resulting from X …
Multichannel blind deconvolution and equalization using the natural gradient
Multichannel deconvolution and equalization is an important task for numerous applications
in communications, signal processing, and control. We extend the efficient natural gradient …
in communications, signal processing, and control. We extend the efficient natural gradient …
Multi-armed bandit-based client scheduling for federated learning
By exploiting the computing power and local data of distributed clients, federated learning
(FL) features ubiquitous properties such as reduction of communication overhead and …
(FL) features ubiquitous properties such as reduction of communication overhead and …
On safeguarding privacy and security in the framework of federated learning
Motivated by the advancing computational capacity of wireless end-user equipment (UE), as
well as the increasing concerns about sharing private data, a new machine learning (ML) …
well as the increasing concerns about sharing private data, a new machine learning (ML) …
Bromodomain 4 activation predicts breast cancer survival
NPS Crawford, J Alsarraj, L Lukes… - Proceedings of the …, 2008 - National Acad Sciences
Previous work identified the Rap1 GTPase-activating protein Sipa1 as a germ-line-encoded
metastasis modifier. The bromodomain protein Brd4 physically interacts with and modulates …
metastasis modifier. The bromodomain protein Brd4 physically interacts with and modulates …
Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes
Purpose: Esophageal squamous cell carcinoma (ESCC) is an aggressive tumor with poor
prognosis. Understanding molecular changes in ESCC will enable identification of …
prognosis. Understanding molecular changes in ESCC will enable identification of …
Age-based scheduling policy for federated learning in mobile edge networks
Federated learning (FL) is a machine learning model that preserves data privacy in the
training process. Specifically, FL brings the model directly to the user equipments (UEs) for …
training process. Specifically, FL brings the model directly to the user equipments (UEs) for …
Heterogeneous cellular network with energy harvesting-based D2D communication
The concept of mobile user equipment (UE) relay (UER) has been introduced to support
device-to-device (D2D) communications for enhancing communication reliability. However …
device-to-device (D2D) communications for enhancing communication reliability. However …