Regularization is a fundamental technique to solve an ill-posed optimization problem
robustly and is essential to reconstruct compressive hyperspectral images. Various hand-crafted …

Due to the long planning horizon, transmission expansion planning is typically subjected to
a lot of uncertainties including load growth, renewable energy penetration, policy changes, …

Ganoderma lucidum is a widely used medicinal macrofungus in traditional Chinese medicine
that creates a diverse set of bioactive compounds. Here we report its 43.3-Mb genome, …

Crop yield is a highly complex trait determined by multiple factors such as genotype, environment,
and their interactions. Accurate yield prediction requires fundamental understanding …

Crop yield prediction is extremely challenging due to its dependence on multiple factors
such as crop genotype, environmental factors, management practices, and their interactions. …

We propose a pseudo-sequence-based scheme for light field image compression. In our
scheme, the raw image captured by a light field camera is decomposed into multiple views …

Lean and Six Sigma methodologies play an important role in the quality and cost driven
world with high competition. In this paper, we develop a unique decision support system that …

This paper presents a unified deep learning framework to recover hyperspectral images
from spectrally undersampled projections. Specifically, we investigate two kinds of …

We present a bilevel optimization approach to designing effective and efficient incentive
policies for stimulating investment in renewable energy. The effectiveness of an incentive policy …

We present an exact algorithm for the bilevel mixed integer linear programming (BMILP)
problem under three simplifying assumptions. Although BMILP has been studied for decades …