D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 45 Citations 7,867 188 World Ranking 3509 National Ranking 326

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Computer network

Shengli Xie mainly focuses on Smart grid, Computer network, Blind signal separation, Matrix decomposition and Algorithm. His work deals with themes such as Distributed algorithm, Distributed computing, Energy management, Energy consumption and Optimization problem, which intersect with Smart grid. The study of Computer network is intertwined with the study of Cognitive radio in a number of ways.

He interconnects Data mining, Multiset, Matrix, Sparse matrix and Component analysis in the investigation of issues within Blind signal separation. The study incorporates disciplines such as Generalization and Feature extraction in addition to Matrix decomposition. His study in Algorithm is interdisciplinary in nature, drawing from both Evolutionary computation, Probabilistic logic and Cluster analysis.

His most cited work include:

  • Home M2M networks: Architectures, standards, and QoS improvement (372 citations)
  • Cognitive machine-to-machine communications: visions and potentials for the smart grid (333 citations)
  • Underdetermined blind source separation based on sparse representation (292 citations)

What are the main themes of his work throughout his whole career to date?

Shengli Xie mostly deals with Algorithm, Artificial intelligence, Cluster analysis, Blind signal separation and Matrix. His research in Algorithm is mostly focused on Sparse approximation. His Sparse approximation study combines topics from a wide range of disciplines, such as Underdetermined system and Sparse matrix.

Shengli Xie has researched Artificial intelligence in several fields, including Machine learning, Computer vision and Pattern recognition. The Cluster analysis study combines topics in areas such as Graph, Subspace topology, Non-negative matrix factorization and Graph. His work is dedicated to discovering how Blind signal separation, Matrix decomposition are connected with Computational complexity theory and other disciplines.

He most often published in these fields:

  • Algorithm (27.02%)
  • Artificial intelligence (21.05%)
  • Cluster analysis (13.33%)

What were the highlights of his more recent work (between 2019-2021)?

  • Algorithm (27.02%)
  • Cluster analysis (13.33%)
  • Matrix (12.98%)

In recent papers he was focusing on the following fields of study:

Shengli Xie focuses on Algorithm, Cluster analysis, Matrix, Artificial intelligence and Matrix decomposition. A large part of his Algorithm studies is devoted to Optimization problem. His Cluster analysis research includes elements of Graph, Feature, Representation, Sparse matrix and Graph.

His Matrix research integrates issues from Time domain, Structure, Blind signal separation, Independent component analysis and Frequency domain. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His research in Matrix decomposition is mostly concerned with Non-negative matrix factorization.

Between 2019 and 2021, his most popular works were:

  • Joint Transaction Relaying and Block Verification Optimization for Blockchain Empowered D2D Communication (13 citations)
  • Non-Negative Matrix Factorization With Dual Constraints for Image Clustering (12 citations)
  • Deep graph regularized non-negative matrix factorization for multi-view clustering (9 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Computer network

Shengli Xie spends much of his time researching Cluster analysis, Algorithm, Matrix, Matrix decomposition and Non-negative matrix factorization. His biological study deals with issues like Graph, which deal with fields such as Graph, Tucker decomposition, Rank and Spectral gap. His research in Algorithm intersects with topics in Representation, Sparse matrix, Unsupervised learning, Fourier transform and Frequency domain.

His studies in Matrix integrate themes in fields like Time domain, Optimization problem, Independent component analysis and Blind signal separation. His research investigates the connection with Matrix decomposition and areas like Computational complexity theory which intersect with concerns in Dimension, Trace, Embedding and Lemma. His work carried out in the field of Artificial intelligence brings together such families of science as Laplacian matrix and Rank.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Home M2M networks: Architectures, standards, and QoS improvement

Yan Zhang;Rong Yu;Shengli Xie;Wenqing Yao.
IEEE Communications Magazine (2011)

478 Citations

Underdetermined blind source separation based on sparse representation

Yuanqing Li;S. Amari;A. Cichocki;D.W.C. Ho.
IEEE Transactions on Signal Processing (2006)

443 Citations

Cognitive machine-to-machine communications: visions and potentials for the smart grid

Yan Zhang;Rong Yu;Maziar Nekovee;Yi Liu.
IEEE Network (2012)

421 Citations

Gradient-Based Structural Similarity for Image Quality Assessment

Guan-Hao Chen;Chun-Ling Yang;Sheng-Li Xie.
international conference on image processing (2006)

323 Citations

Cognitive radio based hierarchical communications infrastructure for smart grid

Rong Yu;Yan Zhang;S. Gjessing;Chau Yuen.
IEEE Network (2011)

293 Citations

An ant colony optimization algorithm for image edge detection

Jing Tian;Weiyu Yu;Shengli Xie.
world congress on computational intelligence (2008)

287 Citations

Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

Jiawen Kang;Rong Yu;Xumin Huang;Maoqiang Wu.
IEEE Internet of Things Journal (2019)

245 Citations

Peak-to-Average Ratio Constrained Demand-Side Management With Consumer's Preference in Residential Smart Grid

Yi Liu;Chau Yuen;Shisheng Huang;Naveed Ul Hassan.
IEEE Journal of Selected Topics in Signal Processing (2014)

210 Citations

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

Derong Liu;Murad Abu-Khalaf;Adel M. Alimi;Charles Anderson.
(2015)

196 Citations

Edge-Based Structural Similarity for Image Quality Assessment

Guan-Hao Chen;Chun-Ling Yang;Lai-Man Po;Sheng-Li Xie.
international conference on acoustics, speech, and signal processing (2006)

177 Citations

Best Scientists Citing Shengli Xie

Yan Zhang

Yan Zhang

Chinese Academy of Sciences

Publications: 65

Andrzej Cichocki

Andrzej Cichocki

Skolkovo Institute of Science and Technology

Publications: 60

Chau Yuen

Chau Yuen

Singapore University of Technology and Design

Publications: 54

C. L. Philip Chen

C. L. Philip Chen

University of Macau

Publications: 43

Rong Yu

Rong Yu

Guangdong University of Technology

Publications: 33

Yun Zhang

Yun Zhang

Guangdong University of Technology

Publications: 33

Nadeem Javaid

Nadeem Javaid

COMSATS University Islamabad

Publications: 30

Sabita Maharjan

Sabita Maharjan

University of Oslo

Publications: 30

Zhi Liu

Zhi Liu

Guangdong University of Technology

Publications: 30

Zidong Wang

Zidong Wang

Brunel University London

Publications: 29

Qibin Zhao

Qibin Zhao

RIKEN

Publications: 22

H. Vincent Poor

H. Vincent Poor

Princeton University

Publications: 22

Guoxu Zhou

Guoxu Zhou

Guangdong University of Technology

Publications: 22

Yan-Jun Liu

Yan-Jun Liu

Liaoning University of Technology

Publications: 20

Ke Zhang

Ke Zhang

Hohai University

Publications: 19

Kun Wang

Kun Wang

University of California, Los Angeles

Publications: 19

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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