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Researcher · Amazon (United States) · United States

Hyokun Yun

Hyokun Yun publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research, on topics such as Topic Modeling, Natural Language Processing Techniques and Machine Learning and Algorithms.

ORCID 0000-0001-6169-4761 OpenAlex
World rank
#1,374,345
of 7,710,434 ranked researchers
Rank in United States
#434,852
of 1,627,098
Works
50
Citations
955
Citations per work
19.1
h-index
10
i10-index 10Top 42% in Artificial Intelligence
Hyokun Yun

What does Hyokun Yun research?

Hyokun Yun's work is mostly in Computer Science (72%), Decision Sciences (6%), Engineering (2%).

Physical Sciences: 37 works · 73.7% of their workComputer Science: 36 works · 71.6% of their workArtificial Intelligence: 27 works · 54.2% of their workComputer Vision and Pattern Recognition: 5 works · 9.7% of their workComputer Networks and Communications: 2 works · 4.9% of their workInformation Systems: 1 works · 2.8% of their workEngineering: 1 works · 2.1% of their workIndustrial and Manufacturing Engineering: 1 works · 2.1% of their workEverything else: 10 works · 20.0% of their workSocial Sciences: 3 works · 6.3% of their workDecision Sciences: 3 works · 6.3% of their workManagement Science and Operations Research: 3 works · 6.3% of their workTHEIR WORKHyokun Yun50works
Physical Sciences74%Social Sciences6%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science3671.6%
    2. Engineering12.1%
  2. Everything else1020.0%
    1. Decision Sciences36.3%
  1. 1Artificial Intelligence54% of their works
  2. 2Computer Vision and Pattern Recognition10% of their works
  3. 3Management Science and Operations Research6% of their works
  4. 4Computer Networks and Communications5% of their works
  5. 5Information Systems3% of their works
  6. 6Industrial and Manufacturing Engineering2% of their works

Research topics

Which keywords describe Hyokun Yun's research?

The keywords of their largest research topics: Neural Networks, Deep Learning, Machine Translation, Word Representation, Neural Machine Translation, Statistical Machine Translation, Semi-Supervised Learning and Active Learning.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 19 words, with their numbers
  1. Neural Networks313 topics
  2. Deep Learning224 topics
  3. Machine Translation201 topic
  4. Word Representation201 topic
  5. Neural Machine Translation121 topic
  6. Statistical Machine Translation121 topic
  7. Semi-Supervised Learning112 topics
  8. Active Learning71 topic
  9. Machine Learning71 topic
  10. Random Projections61 topic
  11. Stochastic Gradient Descent61 topic
  12. Image Captioning51 topic
  13. Markov Decision Processes51 topic
  14. Spoken Dialogue Systems51 topic
  15. Visual Question Answering51 topic
  16. Artificial Intelligence41 topic
  17. Graph Neural Networks41 topic
  18. Knowledge Graph Embedding41 topic
  19. Service Robots41 topic

Where does Hyokun Yun work?

Hyokun Yun's main affiliation in the publication record is Amazon (United States), United States.

How many publications and citations does Hyokun Yun have?

OpenAlex counts 50 works and 955 citations for Hyokun Yun, an h-index of 10, ranking #1,374,345 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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