We study herein an autoregressive model with spatially correlated error terms and missing data. A logistic regression model with completely observed covariates is used to model the missingness mech…
We address a large-scale and nonconvex optimization problem, involving an aggregative term. This term can be interpreted as the sum of the contributions of agents to some common good, with larg…
An narrow linewidth all-optical optomechanically microwave oscillator (OM-MO) based on forward stimulated Brillouin scattering (FSBS) for microwave photonics (MWPs) generation is proposed and demon…
In the present paper, we demonstrate the first outdoor free-space optical communication (FSOC) system with real-time video transmission in a 2-μm-band with a state-of-the-art data rate performance…
In this article, a novel Bayes-Adam-based multiple-input multiple-output (MIMO) equalizer was proposed and experimentally demonstrated for an orbital angular momentum (OAM) mode-division multiplexe…
In the literature of mitigating unfairness in machine learning (ML), many fairness measures are designed to evaluate predictions of learning models and also utilized to guide the training of fair m…
Most types of tunable lasers are sensitive to the ambient temperature and require thermoelectric coolers (TECs) for temperature control. For conventional tunable laser modules, high power consumpti…
We develop a decomposition method based on the augmented Lagrangian framework to solve a broad family of semidefinite programming problems, possibly with nonlinear objective functions, nonsmooth re…
Benefitting from the excellent characteristics such as low cytotoxicity, functionalization versatility, and tunable fluorescence, nanodiamonds (NDs) have shown enormous application potentials in th…
The stochastic block model is one of the most studied network models for community detection, and fitting its likelihood function on large-scale networks is known to be challenging. One prominent w…