most citedGraph Regularized Non-negative Matrix Factorization By Maximizing Correntropy

9 citations · 19 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2014

Hole Detection and Shape-Free Representation and Double Landmarks Based Geographic Routing in Wireless Sensor Networks

Jianjun Yang, Zongming Fei, Ju Shen

In wireless sensor networks, an important issue of Geographic Routing is local minimum problem, which is caused by hole that blocks the greedy forwarding process. To avoid the long…

cs.NI2014

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

Yin Wang, Jianjun Yang, Ju Shen +2

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research com…

cs.IR20148 cited

Document Clustering Based On Max-Correntropy Non-Negative Matrix Factorization

Le Li, Jianjun Yang, Yang Xu +2

Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the $…

cs.CV2014

Structure Preserving Large Imagery Reconstruction

Ju Shen, Jianjun Yang, Sami Taha-abusneineh +2

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for…

cs.NI20142 cited

Location Aided Energy Balancing Strategy in Green Cellular Networks

Jianjun Yang, Bryson Payne, Markus Hitz +3

Most cellular network communication strategies are focused on data traffic scenarios rather than energy balance and efficient utilization. Thus mobile users in hot cells may suffer…

cs.CV20149 cited

Graph Regularized Non-negative Matrix Factorization By Maximizing Correntropy

Le Li, Jianjun Yang, Kaili Zhao +3

Non-negative matrix factorization (NMF) has proved effective in many clustering and classification tasks. The classic ways to measure the errors between the original and the recons…