In this paper, we focus on a novel optimization problem in which the
obj...
Federated Learning (FL) is a promising privacy-preserving distributed
le...
As a promising distributed learning paradigm, federated learning (FL)
in...
As a novel distributed learning paradigm, federated learning (FL) faces
...
The traditional centralized baseband processing architecture is faced wi...
This paper investigates the downlink channel state information (CSI) sen...
Sparse modeling for signal processing and machine learning has been at t...
Federated learning (FL) is a new paradigm that enables many clients to
j...
The impression section of a radiology report summarizes the most promine...
Radiology reports play a critical role in communicating medical findings...
Many existing federated learning (FL) algorithms are designed for superv...
We study a matrix recovery problem with unknown correspondence: given th...
Federated learning (FL) has been recognized as a viable distributed lear...
XGBoost is one of the most widely used machine learning models in the
in...
There has been a growing interest in developing data-driven, and in
part...
Non-negative matrix factorization (NMF) is a powerful tool for dimension...
There has been a growing interest in developing data-driven and in parti...
While many distributed optimization algorithms have been proposed for so...
It is well-known that the problem of finding the optimal beamformers in
...
Medical imaging is frequently used in clinical practice and trials for
d...
Recently, federated learning (FL) has drawn significant attention due to...
This work explores the large-scale multi-agent communication mechanism u...
Distributed learning has become a critical enabler of the massively conn...
The non-negative matrix factorization (NMF) model with an additional
ort...
This paper considers an unmanned-aerial-vehicle-enabled (UAV-enabled)
wi...
This paper investigates energy-efficient resource allocation for the two...
In a full-duplex (FD) multi-user network, the system performance is not ...
In this paper, we consider a scenario where an unmanned aerial vehicle (...
Many contemporary signal processing, machine learning and wireless
commu...
This paper investigates an energy-efficient non-orthogonal transmission
...