15 citations · 34 across the 7 of their papers we have counts for
7 papers
Robust Security Analysis Based on Random Geometry Theory for Satellite-Terrestrial-Vehicle Network
Xudong Li, Ye Fan, Rugui Yao +3
Driven by B5G and 6G technologies, multi-network fusion is an indispensable tendency for future communications. In this paper, we focus on and analyze the \emph{security performanc…
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization
Yuetian Luo, Xudong Li, Anru R. Zhang
In this paper, we propose a general procedure for establishing the geometric landscape connections of a Riemannian optimization problem under the embedded and quotient geometries.…
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
Yuetian Luo, Xudong Li, Anru R. Zhang
In this paper, we consider the geometric landscape connection of the widely studied manifold and factorization formulations in low-rank positive semidefinite (PSD) and general matr…
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence
Yuetian Luo, Wen Huang, Xudong Li +1
In this paper, we propose {\it \underline{R}ecursive} {\it \underline{I}mportance} {\it \underline{S}ketching} algorithm for {\it \underline{R}ank} constrained least squares {\it \…
MixPath: A Unified Approach for One-shot Neural Architecture Search
Xiangxiang Chu, Shun Lu, Xudong Li +1
Blending multiple convolutional kernels is proved advantageous in neural architecture design. However, current two-stage neural architecture search methods are mainly limited to si…
Learning Markov models via low-rank optimization
Ziwei Zhu, Xudong Li, Mengdi Wang +1
Modeling unknown systems from data is a precursor of system optimization and sequential decision making. In this paper, we focus on learning a Markov model from a single trajectory…
Estimation of Markov Chain via Rank-Constrained Likelihood
Xudong Li, Mengdi Wang, Anru Zhang
This paper studies the estimation of low-rank Markov chains from empirical trajectories. We propose a non-convex estimator based on rank-constrained likelihood maximization. Statis…