27 citations · 101 across the 25 of their papers we have counts for
6 papers · 1 filter
Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment
Ghulam A. Qadir, Ying Sun, Sebastian Kurtek
In modeling spatial processes, a second-order stationarity assumption is often made. However, for spatial data observed on a vast domain, the covariance function often varies over…
Semiparametric Estimation of Cross-covariance Functions for Multivariate Random Fields
Ghulam A. Qadir, Ying Sun
The prevalence of spatially referenced multivariate data has impelled researchers to develop a procedure for the joint modeling of multiple spatial processes. This ordinarily invol…
Efficiency Assessment of Approximated Spatial Predictions for Large Datasets
Yiping Hong, Sameh Abdulah, Marc G. Genton +1
Due to the well-known computational showstopper of the exact Maximum Likelihood Estimation (MLE) for large geospatial observations, a variety of approximation methods have been pro…
A Unified Contraction Analysis of a Class of Distributed Algorithms for Composite Optimization
Jinming Xu, Ying Sun, Ye Tian +1
We study distributed composite optimization over networks: agents minimize the sum of a smooth (strongly) convex function, the agents' sum-utility, plus a non-smooth (extended-valu…
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
Jinming Xu, Ye Tian, Ying Sun +1
This paper proposes a novel family of primal-dual-based distributed algorithms for smooth, convex, multi-agent optimization over networks that uses only gradient information and go…
Asynchronous Decentralized Successive Convex Approximation
Ye Tian, Ying Sun, Gesualdo Scutari
We study decentralized asynchronous multiagent optimization over networks, modeled as static (possibly directed) graphs. The optimization problem consists of minimizing a (possibly…