H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 61 Citations 43,167 188 World Ranking 1500 National Ranking 831

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Artificial intelligence, Machine learning, Text categorization, Information retrieval and Language model are his primary areas of study. His studies deal with areas such as Ranking and Natural language processing as well as Artificial intelligence. He combines subjects such as Noise reduction, Autoregressive model and Pattern recognition with his study of Machine learning.

His studies in Text categorization integrate themes in fields like Supervised learning and Coding. His work on Relevance as part of general Information retrieval study is frequently linked to Original data and Backlink, therefore connecting diverse disciplines of science. His work deals with themes such as Theoretical computer science, Contextual image classification, Reinforcement learning, Treebank and Search algorithm, which intersect with Language model.

His most cited work include:

  • A Comparative Study on Feature Selection in Text Categorization (4440 citations)
  • A re-examination of text categorization methods (2372 citations)
  • RCV1: A New Benchmark Collection for Text Categorization Research (2193 citations)

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

His main research concerns Artificial intelligence, Machine learning, Natural language processing, Information retrieval and Data mining. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition. Machine learning is closely attributed to Scalability in his research.

His work in the fields of Natural language processing, such as Cross lingual and Sentence, overlaps with other areas such as Variety and Domain. His Relevance, Vector space model and Search engine indexing study, which is part of a larger body of work in Information retrieval, is frequently linked to Set, bridging the gap between disciplines. His Data mining research includes elements of Adaptive filter and Cluster analysis.

He most often published in these fields:

  • Artificial intelligence (68.92%)
  • Machine learning (40.09%)
  • Natural language processing (24.32%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (68.92%)
  • Machine learning (40.09%)
  • Natural language processing (24.32%)

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

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Natural language processing, Language model and Benchmark. The concepts of his Artificial intelligence study are interwoven with issues in Multivariate statistics and Code. The Machine learning study which covers Autoregressive model that intersects with Algorithm.

Many of his research projects under Natural language processing are closely connected to Set and Pipeline with Set and Pipeline, tying the diverse disciplines of science together. His Language model research is multidisciplinary, incorporating perspectives in Question answering and Treebank. In his study, Artificial neural network is inextricably linked to Matching, which falls within the broad field of Word.

Between 2017 and 2021, his most popular works were:

  • XLNet: Generalized Autoregressive Pretraining for Language Understanding (1425 citations)
  • XLNet: Generalized Autoregressive Pretraining for Language Understanding (1165 citations)
  • DARTS: Differentiable Architecture Search (1007 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Yiming Yang mainly investigates Artificial intelligence, Machine learning, Language model, Transformer and Question answering. His Artificial intelligence study frequently links to other fields, such as Natural language processing. His work carried out in the field of Natural language processing brings together such families of science as Joint and Benchmark.

Within one scientific family, Yiming Yang focuses on topics pertaining to Autoregressive model under Machine learning, and may sometimes address concerns connected to Margin, Sentiment analysis, Dependency, Noise reduction and Ranking. His work investigates the relationship between Language model and topics such as Treebank that intersect with problems in Perplexity and Speech recognition. His biological study spans a wide range of topics, including Mobile device, F1 score, Computer engineering and Empirical research.

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.

Top Publications

A Comparative Study on Feature Selection in Text Categorization

Yiming Yang;Jan O. Pedersen.
international conference on machine learning (1997)

7627 Citations

A re-examination of text categorization methods

Yiming Yang;Xin Liu.
international acm sigir conference on research and development in information retrieval (1999)

4131 Citations

An Evaluation of Statistical Approaches to Text Categorization

Yiming Yang.
Information Retrieval (1999)

3124 Citations

RCV1: A New Benchmark Collection for Text Categorization Research

David D. Lewis;Yiming Yang;Tony G. Rose;Fan Li.
Journal of Machine Learning Research (2004)

3008 Citations

Topic Detection and Tracking Pilot Study Final Report

James Allan;Jaime Carbonell;George Doddington;Jonathan Yamron.
Proceedings of the Broadcast News Transcription and Understanding Workshop (Sponsored by DARPA) (1998)

1454 Citations

The enron corpus: a new dataset for email classification research

Bryan Klimt;Yiming Yang.
european conference on machine learning (2004)

1178 Citations

DARTS: Differentiable Architecture Search

Hanxiao Liu;Karen Simonyan;Yiming Yang.
international conference on learning representations (2018)

1055 Citations

A study of retrospective and on-line event detection

Yiming Yang;Tom Pierce;Jaime Carbonell.
international acm sigir conference on research and development in information retrieval (1998)

1022 Citations

Introducing the Enron Corpus.

Bryan Klimt;Yiming Yang.
conference on email and anti-spam (2004)

794 Citations

Transformer-XL: Attentive Language Models beyond a Fixed-Length Context.

Zihang Dai;Zhilin Yang;Yiming Yang;Jaime G. Carbonell.
meeting of the association for computational linguistics (2019)

732 Citations

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

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