Who Cited It

A few useful things to know about machine learning

2012 · Communications of the ACM · 3,338 citations · 4 from inside this corpus

Pedro Domingos

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

A few useful things to know about machine learning (2012)A few useful things to know a…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…C4.5: Programs for Machine Learning (1992)C4.5: Programs for Machine Le…Causality (2009)CausalityLearning Deep Architectures for AI (2009)Learning Deep Architectures f…Learning Deep Architectures for AI (2009)Learning Deep Architectures f…Causality: Models, Reasoning and Inference (2001)Causality: Models, Reasoning …On the Optimality of the Simple Bayesian Classifier under Zero-One Loss (1997)On the Optimality of the Simp…Causality: models, reasoning, and inference (2000)Causality: models, reasoning,…Markov logic networks (2006)Markov logic networksAn Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… (1999)An Empirical Comparison of Vo…Bayesian Theory (1994)Bayesian TheoryThe Lack of A Priori Distinctions Between Learning Algorithms (1996)The Lack of A Priori Distinct…Deep learning applications and challenges in big data analytics (2015)Deep learning applications an…Deep Learning for Health Informatics (2016)Deep Learning for Health Info…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health R… (2017)Deep EHR: A Survey of Recent …
16 of 16 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.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
The Nature of Statistical Learning Theory199539,409
C4.5: Programs for Machine Learning199223,704
Causality200911,477
Learning Deep Architectures for AI20096,951
Learning Deep Architectures for AI20095,077
Causality: Models, Reasoning and Inference20014,831
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss19973,099
Causality: models, reasoning, and inference20002,920
Markov logic networks20062,684
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
Bayesian Theory19942,168
The Lack of A Priori Distinctions Between Learning Algorithms19961,661

What cites it, inside the corpus

PaperYearCited
Deep learning applications and challenges in big data analytics20152,610
Deep Learning for Health Informatics20162,015
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]1,853
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health R…20171,693

Links

DOI · OpenAlex record

Topics

Machine Learning and Data ClassificationComputer Science
Bayesian Modeling and Causal InferenceComputer Science
Machine Learning and AlgorithmsComputer Science

Is this record sound?

complete

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

  • supports1 author record(s) attached.
  • supports31 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 2026-09-04T03:58:47+00:00.

sha256 a08467ae9504f237…