3 accepted papers
Time-varying graphical LASSO (TVGL) aims to infer a sequence of graphs from time series data and has been widely used in many statistical inference problems. The existing algorithms usually suffer from high computational cost when solving large-scale TVGL problems. In this paper, we develop an effic…
Optimization problems with access to only zeroth-order information of the objective function on Riemannian manifolds arise in various applications, spanning from statistical learning to robot learning. While various zeroth-order algorithms have been proposed in Euclidean space, they are not inherent…
Decentralized optimization aims to cooperatively solve a global finite-sum loss function, where each agent only possesses knowledge of its own local function. Real-world applications introduce challenges such as unstable channels and differential privacy concerns, necessitating the development of mo…