mlsanityData to 7 Oct 2026

Patterns, predictions, and actions: A story about machine learning

arXiv 2102.05242 ↗First posted 10 Feb 2021cs.LG stat.MLcited by 14

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Abstract (arXiv)

This graduate textbook on machine learning tells a story of how patterns in data support predictions and consequential actions. Starting with the foundations of decision making, we cover representation, optimization, and generalization as the constituents of supervised learning. A chapter on datasets as benchmarks examines their histories and scientific bases. Self-contained introductions to causality, the practice of causal inference, sequential decision making, and reinforcement learning equip the reader with concepts and tools to reason about actions and their consequences. Throughout, the text discusses historical context and societal impact. We invite readers from all backgrounds; some experience with probability, calculus, and linear algebra suffices.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 20 of its 256 references that are in the map. First posted on arXiv 10 Feb 2021.

Builds on

20 of 256 references.

References · 20

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,590
  3. 2018Neural Tangent Kernel: Convergence and Generalization in Neural Networkscited by 2,597
  4. 2016Understanding deep learning requires rethinking generalizationcited by 1,657
  5. 2018Datasheets for Datasetscited by 1,371
  6. 2015Estimation and Inference of Heterogeneous Treatment Effects using Random Forestscited by 597
  7. 2017Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Datacited by 527
  8. 2014In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learningcited by 339
  9. 2018Stronger generalization bounds for deep nets via a compression approachcited by 306
  10. 2019Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Themcited by 268
  11. 2020Data and its (dis)contents: A survey of dataset development and use in machine learning researchcited by 259
  12. 2019Causality for Machine Learningcited by 242
8 more
  1. 2018A Tour of Reinforcement Learning: The View from Continuous Controlcited by 129
  2. 2014Preserving Statistical Validity in Adaptive Data Analysiscited by 102
  3. 201850 Years of Test (Un)fairness: Lessons for Machine Learningcited by 101
  4. 2015Why Random Reshuffling Beats Stochastic Gradient Descentcited by 78
  5. 2018A Contextual Bandit Bake-offcited by 64
  6. 2021Interpolating Classifiers Make Few Mistakescited by 22
  7. 2020Why do classifier accuracies show linear trends under distribution shift?cited by 21
  8. 2017Fair prediction with disparate impact: A study of bias in recidivism prediction instrumentscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 7; 2023: 2; 2024: 1; 2025: 1; 2026: 1.

14 papers.

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  1. 2021Retiring Adult: New Datasets for Fair Machine Learningcited by 443
  2. 2022Loss Minimization through the Lens of Outcome Indistinguishabilitycited by 61
  3. 2023Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusioncited by 39
  4. 2022Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guaranteescited by 34
  5. 2022Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasetscited by 7
  6. 2022Adversarial Scrutiny of Evidentiary Statistical Softwarecited by 5
  7. 2022Context matters for fairness -- a case study on the effect of spatial distribution shiftscited by 3
  8. 2022Sampling from Pre-Images to Learn Heuristic Functions for Classical Planningcited by 3
  9. 2023Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecturecited by 1
  10. 2026Decision-Aligned Evaluation of Uncertainty Quantificationcited by 1
  11. 2021Machine learning in the social and health sciencescited by 0
  12. 2022Studying Generalization Through Data Averagingcited by 0
2 more
  1. 2024Accelerated AI Inference via Dynamic Execution Methodscited by 0
  2. 2025Stability Regularized Cross-Validationcited by 0