Compressed sensing is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Sparse coding represents a signal as a sparse linear combination of …
W Shi, Q Ling, G Wu, W Yin - IEEE Transactions on Signal …, 2015 - ieeexplore.ieee.org
This paper proposes a decentralized algorithm for solving a consensus optimization problem defined in a static networked multi-agent system, where the local objective …
J Zeng, W Yin - IEEE Transactions on signal processing, 2018 - ieeexplore.ieee.org
Consensus optimization has received considerable attention in recent years. A number of decentralized algorithms have been proposed for convex consensus optimization. However …
NS Aybat, Z Wang, T Lin, S Ma - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Given an undirected graph G=(N, E) of agents N={1,..., N} connected with edges in E, we study how to compute an optimal decision on which there is consensus among agents and …
Accurate and automatic multi-needle detection in three-dimensional (3D) ultrasound (US) is a key step of treatment planning for US-guided brachytherapy. However, most current …
This is an introduction to multicast routing, which is the study of methods for routing from one source to many destinations, or from many sources to many destinations. Multicast is …
The alternating direction method of multipliers (ADMM) has been recently recognized as a promising optimizer for large-scale machine learning models. However, there are very few …
J Liu, K Huang, X Yao - IEEE Sensors Journal, 2018 - ieeexplore.ieee.org
We study the sparse signal reconstruction problem in a wireless sensor network (WSN) using distributed compressed sensing. The sparse signals from multiple sensors are …
SM Fosson - IEEE Transactions on Automatic Control, 2020 - ieeexplore.ieee.org
The development of online algorithms to track time-varying systems has drawn a lot of attention in the last years, in particular in the framework of online convex optimization …