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Topic · Artificial Intelligence

Machine Learning and Algorithms

Machine Learning and Algorithms is a research topic within Artificial Intelligence. Science Explorer counts 18k research works in it since 1954. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers revolves around the topic of active learning in machine learning research. It covers various aspects such as semi-supervised learning, deep learning, Gaussian processes, image classification, text categorization, batch mode active learning, statistical guarantees, and human-in-the-loop approaches.

  • Active Learning
  • Machine Learning
  • Semi-supervised Learning
  • Deep Learning
  • Gaussian Processes
  • Image Classification
  • Text Categorization
  • Batch Mode
  • Statistical Guarantees
  • Human-in-the-loop
Research works
18k
fractional, since 1954
In the world top 10%
1.7k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+10%
the tick is no change
Largest producer
United States
33% of the 10 largest, 2022-now
Machine Learning and Algorithms

Which countries lead Machine Learning and Algorithms research?

By volume, the United States and China publish the most (842 and 658 works in 2022-now).

By volume, 2022-now

  1. 1 United States 842 works
  2. 2 China 658 works
  3. 3 Germany 224 works
  4. 4 United Kingdom 167 works
  5. 5 India 139 works
  6. 6 France 137 works
  7. 7 Japan 114 works
  8. 8 Canada 99 works
  9. 9 Italy 97 works
  10. 10 Australia 70 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 33.1%China: 25.9%Germany: 8.8%United Kingdom: 6.6%6 others listed: 25.7%33%largest
United States842 · 33.1%China658 · 25.9%Germany224 · 8.8%United Kingdom167 · 6.6%6 others listed654 · 25.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Machine Learning and Algorithms research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Machine Learning and Algorithms research, followed by Chinese Academy of Sciences and Massachusetts Institute of Technology.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 47 works
  2. 2 Chinese Academy of SciencesChina 29 works
  3. 3 Massachusetts Institute of TechnologyUnited States 24 works
  4. 4 University of California, BerkeleyUnited States 24 works
  5. 5 Stanford UniversityUnited States 22 works
  6. 6 Carnegie Mellon UniversityUnited States 22 works
  7. 7 National University of SingaporeSingapore 21 works
  8. 8 Tsinghua UniversityChina 20 works
  9. 9 Alphabet (United States)United States 19 works
  10. 10 Shanghai Jiao Tong UniversityChina 17 works

Who are the leading researchers in Machine Learning and Algorithms?

The most-cited researchers publishing on Machine Learning and Algorithms include Yoshua Bengio, Geoffrey E. Hinton and Robert John Tibshirani.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Geoffrey E. Hinton Canada 454k citations
  3. 3 Robert John Tibshirani United States 396k citations
  4. 4 Steven L. Salzberg United States 372k citations
  5. 5 Karl John Friston United Kingdom 310k citations
  6. 6 Trevor Hastie United States 301k citations
  7. 7 Yann LeCun United States 256k citations
  8. 8 Andrew Zisserman United Kingdom 255k citations
  9. 9 Vladimir N. Vapnik United States 227k citations
  10. 10 Li Fei-Fei United States 225k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Machine Learning and Algorithms?

The most cited paper in Machine Learning and Algorithms is "XGBoost" (Tianqi Chen, Carlos Guestrin, 2016), with 53,418 citations. Next come "Dropout: a simple way to prevent neural networks from overfitting" (34,210) and "Greedy function approximation: A gradient boosting machine." (30,593).

Most cited papers
#PaperReleasedCitations
1 XGBoost Tianqi Chen, Carlos Guestrin Conference paperOpen access 8 Aug 2016 53,418
2 Dropout: a simple way to prevent neural networks from overfitting Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky et al. 2014 34,210
3 Greedy function approximation: A gradient boosting machine. Jerome H. Friedman · The Annals of Statistics Oct 2001 30,593
4 Random sample consensus Martin A. Fischler, Robert C. Bolles · Communications of the ACM Open access Jun 1981 26,036
5 A Survey on Transfer Learning Sinno Jialin Pan, Qiang Yang · IEEE Transactions on Knowledge and Data Engineering 16 Oct 2009 23,834
All 98 most cited papers, with filters and sorting

Where is Machine Learning and Algorithms research done?

The largest centres of Machine Learning and Algorithms research in 2022-now are Beijing (China), Shanghai (China), Tokyo (Japan) and Nanjing (China).

Largest cities, 2022-now

  1. 1 BeijingChina 148 works
  2. 2 ShanghaiChina 61 works
  3. 3 TokyoJapan 51 works
  4. 4 NanjingChina 47 works
  5. 5 ParisFrance 46 works
  6. 6 LondonUnited Kingdom 43 works
  7. 7 SingaporeSingapore 41 works
  8. 8 SeoulSouth Korea 38 works
  9. 9 New YorkUnited States 37 works
  10. 10 Hong KongChina 34 works
See Machine Learning and Algorithms on the map

Where is the best place to study Machine Learning and Algorithms?

Among universities, judged by research, Chinese University of Hong Kong, University of California, Berkeley and Massachusetts Institute of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%10%20%30%mean 17.34%fractional works in this field (log) →share of work in the world top 10% →Chinese University o…Hong Kong University…University of Califo…Massachusetts Instit…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Chinese University of Hong KongChina 69.226.3%4.8×10 +83.2%
2University of California, BerkeleyUnited States 64.712.0%8.6×24 -17.7%
3Massachusetts Institute of TechnologyUnited States 63.510.5%11.9×24 -45.6%
4Hong Kong University of Science and TechnologyChina 63.218.7%8.2×10 +45.2%
5Carnegie Mellon UniversityUnited States 63.013.5%18.1×22 -68.5%
6Stanford UniversityUnited States 61.012.2%5.1×22 -46.4%
7Xidian UniversityChina 56.525.2%4.0×8 +185.2%
8Tsinghua UniversityChina 56.017.6%3.0×20 +0.8%
9Tianjin UniversityChina 54.326.3%2.4×8 +229.8%
10Georgia Institute of TechnologyUnited States 53.311.1%9.5×17 +4.4%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Machine Learning and Algorithms, country by country

Is Machine Learning and Algorithms research growing?

Output in 2022-2025 was 10% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Machine Learning and Algorithms.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Machine Learning and Algorithms as a percentage of every work published that year, 0.014% in 2024.

still counting0.020%0.040%Machine Learning and Algorithms0.014% in 202519801990200020102020

Fractional works of Machine Learning and Algorithms over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Machine Learning and Algorithms9.9% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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