Saudi scientists created a new deep learning technique based on distributionally robust optimization (DRO) to identify the most suitable locations for utility scale wind and solar power projects. They ...

Abstract: Drawing on the minimization of worst-case maximum likelihood (ML) estimation, this article develops a robust inverse clutter-plus-noise covariance matrix (CNCM) estimator for space–time ...

Abstract: With an extensive increment of computation demands, the aerial multi-access edge computing (MEC), mainly based on uncrewed aerial vehicles (UAVs) and high altitude platforms (HAPs), plays ...

DR-GEM is a self-supervised meta-algorithm that combines principles in distributionally robust optimization with balanced consensus machine learning to overcome the challenges of latent class ...

Goh, Joel, and Melvyn Sim. "Distributionally Robust Optimization and Its Tractable Approximations." Operations Research 58, no. 4 (pt.1) (July–August 2010): 902–917.

Source codes for research paper: Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval, Guangyuan Ma, Yongliang Ma, Xing Wu, Zhenpeng Su, Ming Zhou and Songlin ...

We consider sensitivity of a generic stochastic optimization problem to model uncertainty. We take a non-parametric approach and capture model uncertainty using Wasserstein balls around the postulated ...

Discover the future of satellite technology with space computing power networks (Space-CPN). This innovative architecture ...