The optimal implementation of federated learning (FL) in practical edge
...
Low-rank model compression is a widely used technique for reducing the
c...
The optimal design of federated learning (FL) algorithms for solving gen...
Optimal algorithm design for federated learning (FL) remains an open pro...
Sparse coding is a class of unsupervised methods for learning a sparse
r...
Dictionary learning is a widely used unsupervised learning method in sig...
Wireless backhaul is considered to be the key part of the future wireles...
Massive MIMO has been regarded as a key enabling technique for 5G and be...
Dictionary learning is a classic representation learning method that has...
This paper proposes an efficient algorithm for designing the
distance-sp...
In this paper, we consider the problem of stochastic optimization, where...
We consider the uplink of a cloud radio access network (C-RAN), where ma...
Recently, physical layer (PHY) caching has been proposed to exploit the
...
Hybrid precoding, which consists of an RF precoder and a baseband precod...
This paper proposes a constrained stochastic successive convex approxima...