Who Cited It

Introduction to Machine Learning

2019 · Springer briefs in electrical and computer engineering · 1,620 citations · 0 from inside this corpus

F. Richard Yu, Ying He

No abstract in the source record.

Introduction to Machine Learning (2019)Introduction to Machine Learn…Random Forests (2001)Random ForestsLong Short-Term Memory (1997)Long Short-Term MemoryNeural Networks: A Comprehensive Foundation (1998)Neural Networks: A Comprehens…Statistical Learning Theory (1999)Statistical Learning TheoryA tutorial on hidden Markov models and selected applications in speech recognition (1989)A tutorial on hidden Markov m…Classification and Regression Trees. (1986)Classification and Regression…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Induction of Decision Trees (1986)Induction of Decision TreesNeural networks: A comprehensive foundation (1995)Neural networks: A comprehens…Bayesian Network Classifiers (1997)Bayesian Network ClassifiersBayesian Networks and Decision Graphs (2007)Bayesian Networks and Decisio…Supervised Machine Learning: A Review of Classification Techniques (2007)Supervised Machine Learning: …Long short-term memory recurrent neural network architectures for large scale acoustic mo… (2014)Long short-term memory recurr…Introduction to Bayesian Networks (2019)Introduction to Bayesian Netw…The self-organizing map (1998)The self-organizing mapA Tutorial on Learning with Bayesian Networks (2008)A Tutorial on Learning with B…Extensions of recurrent neural network language model (2011)Extensions of recurrent neura…Support Vector Machines (2020)Support Vector Machines
18 of 18 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Random Forests2001131,109
Long Short-Term Memory1997101,359
Neural Networks: A Comprehensive Foundation199829,840
Statistical Learning Theory199926,957
A tutorial on hidden Markov models and selected applications in speech recognition198922,910
Classification and Regression Trees.198621,044
Deep learning in neural networks: An overview201418,236
Induction of Decision Trees198615,020
Neural networks: A comprehensive foundation19957,270
Bayesian Network Classifiers19974,754
Bayesian Networks and Decision Graphs20074,152
Supervised Machine Learning: A Review of Classification Techniques20074,149
Long short-term memory recurrent neural network architectures for large scale acoustic mo…20142,986
Introduction to Bayesian Networks20192,594
The self-organizing map19981,982
A Tutorial on Learning with Bayesian Networks20081,715
Extensions of recurrent neural network language model20111,603
Support Vector Machines20201,484

Links

DOI · OpenAlex record

Topics

Anomaly Detection Techniques and ApplicationsComputer Science
Neural Networks and ApplicationsComputer Science
Machine Learning and Data ClassificationComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports2 author record(s) attached.
  • supports53 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

sha256 7bc26169e93749d1…