38 citations · 71 across the 16 of their papers we have counts for
16 papers
Network Topology Inference from Smooth Signals Under Partial Observability
Chuansen Peng, Hanning Tang, Zhiguo Wang +1
Inferring network topology from smooth signals is a significant problem in data science and engineering. A common challenge in real-world scenarios is the availability of only part…
An Accelerated Stochastic ADMM for Nonconvex and Nonsmooth Finite-Sum Optimization
Yuxuan Zeng, Zhiguo Wang, Jianchao Bai +1
The nonconvex and nonsmooth finite-sum optimization problem with linear constraint has attracted much attention in the fields of artificial intelligence, computer, and mathematics,…
Nonlinear Set Membership Filter with State Estimation Constraints via Consensus-ADMM
Xiaowei Li, Xuqi Zhang, Zhiguo Wang +1
This paper considers the state estimation problem for nonlinear dynamic systems with unknown but bounded noises. Set membership filter (SMF) is a popular algorithm to solve this pr…
Distributed Scaled Proximal ADMM Algorithms for Cooperative Localization in WSNs
Mei Zhang, Zhiguo Wang, Feng Yin +1
Distributed cooperative localization in wireless networks is a challenging problem since it typically requires solving a large-scale nonconvex and nonsmooth optimization problem. I…
An Unbiased Symmetric Matrix Estimator for Topology Inference under Partial Observability
Yupeng Chen, Zhiguo Wang, Xiaojing Shen
Network topology inference is a fundamental problem in many applications of network science, such as locating the source of fake news, brain connectivity networks detection, etc. M…
Towards Understanding the Impact of Model Size on Differential Private Classification
Yinchen Shen, Zhiguo Wang, Ruoyu Sun +1
Differential privacy (DP) is an essential technique for privacy-preserving. It was found that a large model trained for privacy preserving performs worse than a smaller model (e.g.…