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 44 Citations 8,413 146 World Ranking 3699 National Ranking 1892

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Artificial intelligence, Data mining, Distributed computing, Deep learning and Theoretical computer science. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition. While the research belongs to areas of Data mining, Yixin Chen spends his time largely on the problem of Data stream clustering, intersecting his research to questions surrounding Data stream mining, Canopy clustering algorithm and Determining the number of clusters in a data set.

Yixin Chen combines subjects such as Web service and Network topology, Wireless sensor network, Computer network, Scheduling with his study of Distributed computing. His Deep learning study integrates concerns from other disciplines, such as End-to-end principle and Graph classification. His studies in Theoretical computer science integrate themes in fields like STRIPS, Algorithm, Scalability and Key.

His most cited work include:

  • Compressing Neural Networks with the Hashing Trick (445 citations)
  • An End-to-End Deep Learning Architecture for Graph Classification. (409 citations)
  • Density-based clustering for real-time stream data (397 citations)

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

The scientist’s investigation covers issues in Artificial intelligence, Mathematical optimization, Data mining, Machine learning and Theoretical computer science. His Artificial intelligence study frequently draws connections between adjacent fields such as Pattern recognition. The study incorporates disciplines such as Algorithm and Nonlinear programming in addition to Mathematical optimization.

The Data mining study combines topics in areas such as Data stream clustering and Cluster analysis. His studies in Feature and Categorical variable are all subfields of Machine learning research. His work in Theoretical computer science addresses subjects such as Heuristics, which are connected to disciplines such as Scalability.

He most often published in these fields:

  • Artificial intelligence (23.97%)
  • Mathematical optimization (24.72%)
  • Data mining (12.36%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (23.97%)
  • Theoretical computer science (11.99%)
  • Graph (5.62%)

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

His primary areas of investigation include Artificial intelligence, Theoretical computer science, Graph, Artificial neural network and Machine learning. His studies deal with areas such as Postoperative mortality, MEDLINE and Pattern recognition as well as Artificial intelligence. His Graph research includes elements of Transfer of learning, Bayesian network, Domain knowledge and Graph.

In his research, Linear model, Generalized additive model, Feature, Variety and Big data is intimately related to Support vector machine, which falls under the overarching field of Artificial neural network. His Machine learning study combines topics in areas such as Data modeling and Asset. Yixin Chen has researched Similarity in several fields, including Sampling and Data mining.

Between 2018 and 2021, his most popular works were:

  • D-VAE: A Variational Autoencoder for Directed Acyclic Graphs (37 citations)
  • Time series feature learning with labeled and unlabeled data (25 citations)
  • Inductive Matrix Completion Based on Graph Neural Networks (19 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Theoretical computer science, Artificial intelligence, Graph, Graph and Pattern recognition are his primary areas of study. His work in Theoretical computer science addresses issues such as Artificial neural network, which are connected to fields such as Anesthesia. His research related to Random forest, Deep learning and Feature selection might be considered part of Artificial intelligence.

His Deep learning research incorporates elements of Receiver operating characteristic, Logistic regression, Convolutional neural network and Confidence interval. His Pattern recognition study which covers Time series that intersects with Feature extraction, Regularized least squares and Statistical significance. His biological study spans a wide range of topics, including Semi-supervised learning, Data modeling, Training set, Data mining and Regularization.

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

Density-based clustering for real-time stream data

Yixin Chen;Li Tu.
knowledge discovery and data mining (2007)

652 Citations

An End-to-End Deep Learning Architecture for Graph Classification.

Muhan Zhang;Zhicheng Cui;Marion Neumann;Yixin Chen.
national conference on artificial intelligence (2018)

488 Citations

Compressing Neural Networks with the Hashing Trick

Wenlin Chen;James Wilson;Stephen Tyree;Stephen Tyree;Kilian Weinberger.
arXiv: Learning (2015)

487 Citations

Multi-dimensional regression analysis of time-series data streams

Yixin Chen;Guozhu Dong;Jiawei Han;Benjamin W. Wah.
very large data bases (2002)

454 Citations

Real-Time Scheduling for WirelessHART Networks

Abusayeed Saifullah;You Xu;Chenyang Lu;Yixin Chen.
real-time systems symposium (2010)

257 Citations

Multi-Scale Convolutional Neural Networks for Time Series Classification

Zhicheng Cui;Wenlin Chen;Yixin Chen.
arXiv: Computer Vision and Pattern Recognition (2016)

251 Citations

Real-Time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systems

Chenyang Lu;Abusayeed Saifullah;Bo Li;Mo Sha.
Proceedings of the IEEE (2016)

248 Citations

Temporal planning using subgoal partitioning and resolution in SGPlan

Yixin Chen;Benjamin W. Wah;Chih-Wei Hsu.
Journal of Artificial Intelligence Research (2006)

236 Citations

Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams

Jiawei Han;Yixin Chen;Guozhu Dong;Jian Pei.
Distributed and Parallel Databases (2005)

231 Citations

Link prediction based on graph neural networks

Muhan Zhang;Yixin Chen.
neural information processing systems (2018)

217 Citations

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Best Scientists Citing Yixin Chen

Jiawei Han

Jiawei Han

University of Illinois at Urbana-Champaign

Publications: 38

Chenyang Lu

Chenyang Lu

Washington University in St. Louis

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Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

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Dacheng Tao

Dacheng Tao

University of Sydney

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Charu C. Aggarwal

Charu C. Aggarwal

IBM (United States)

Publications: 18

Chang Xu

Chang Xu

University of Sydney

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Michalis Vazirgiannis

Michalis Vazirgiannis

École Polytechnique

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Thomas Seidl

Thomas Seidl

Ludwig-Maximilians-Universität München

Publications: 17

Jure Leskovec

Jure Leskovec

Stanford University

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Venkatesh Saligrama

Venkatesh Saligrama

Boston University

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Shuiwang Ji

Shuiwang Ji

Texas A&M University

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Guoliang Xing

Guoliang Xing

Chinese University of Hong Kong

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Kilian Q. Weinberger

Kilian Q. Weinberger

Cornell University

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Haixun Wang

Haixun Wang

Instacart

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Alfredo Cuzzocrea

Alfredo Cuzzocrea

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Qi Tian

Qi Tian

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