Substantial progress has been made recently on develo** provably accurate and efficient
algorithms for low-rank matrix factorization via nonconvex optimization. While conventional …

Abstract Graph Neural Networks (GNNs) have achieved great success in representing data
with dependencies by recursively propagating and aggregating messages along the edges …

This paper tackles the problem of joint active and passive beamforming optimization for an
intelligent reflective surface (IRS)-assisted multi-user downlink multiple-input multiple-output …

We consider distributed smooth nonconvex unconstrained optimization over net-works,
modeled as a connected graph. We examine the behavior of distributed gradient-based …

We consider the problem of joint unicast and multi-group multicast beamforming design for
large-scale massive multiple-input multiple-output (MIMO) systems, with a potentially large …

Due to the poorly coupled geophones present in boreholes, vertical seismic profiling (VSP)
data are known to suffer from intense coupling noise, which causes severe VSP image …

We examine the problem of joint active and passive beamforming in a controllable multi-
user reconfigurable intelligent surface (RIS)-assisted downlink and uplink wireless …

Benefiting from exploiting the waveform superposition property in the multi-access channels,
over-the-air computation (AirComp) has emerged as a promising technique to swiftly …

This paper considers general rank-constrained optimization problems that minimize a
general objective function over the set of rectangular matrices that have rank at most r. To …

Over-the-air computation (AirComp) has been recognized as a low-latency solution for
wireless sensor data fusion, where multiple sensors send their measurement signals to a …