mlsanityData to 14 Oct 2026

Artificial Intelligence and Statistics

arXiv 1712.03779 ↗First posted 8 Dec 2017stat.ML cs.AIcited by 43

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Abstract (arXiv)

Artificial intelligence (AI) is intrinsically data-driven. It calls for the application of statistical concepts through human-machine collaboration during generation of data, development of algorithms, and evaluation of results. This paper discusses how such human-machine collaboration can be approached through the statistical concepts of population, question of interest, representativeness of training data, and scrutiny of results (PQRS). The PQRS workflow provides a conceptual framework for integrating statistical ideas with human input into AI products and research. These ideas include experimental design principles of randomization and local control as well as the principle of stability to gain reproducibility and interpretability of algorithms and data results. We discuss the use of these principles in the contexts of self-driving cars, automated medical diagnoses, and examples from the authors' collaborative research.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Dec 2017.

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Citing papers per year: 2021: 13; 2022: 7; 2023: 10; 2024: 4; 2025: 4; 2026: 5.

43 papers.

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  1. 2021StyleSwin: Transformer-based GAN for High-resolution Image Generationcited by 152
  2. 2023ALIP: Adaptive Language-Image Pre-training with Synthetic Captioncited by 70
  3. 2021FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learningcited by 39
  4. 2022Learning on Arbitrary Graph Topologies via Predictive Codingcited by 33
  5. 2022Learning Causal Effects on Hypergraphscited by 31
  6. 2023A Primer on Bayesian Neural Networks: Review and Debatescited by 27
  7. 2021Fixed-Budget Best-Arm Identification in Structured Banditscited by 22
  8. 2021A Vertical Federated Learning Framework for Graph Convolutional Networkcited by 21
  9. 2024Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalizationcited by 20
  10. 2022SCOTCH and SODA: A Transformer Video Shadow Detection Frameworkcited by 19
  11. 2021Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networkscited by 14
  12. 2023Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequencescited by 14
31 more
  1. 2022Causal Entropy Optimizationcited by 13
  2. 2021Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networkscited by 10
  3. 2021Loss Tolerant Federated Learningcited by 8
  4. 2024Boosting Adversarial Training via Fisher-Rao Norm-based Regularizationcited by 7
  5. 2022CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learningcited by 6
  6. 2025Game State and Spatio-temporal Action Detection in Soccer using Graph Neural Networks and 3D Convolutional Networkscited by 6
  7. 2025CSD-VAR: Content-Style Decomposition in Visual Autoregressive Modelscited by 6
  8. 2023Unbinned Profiled Unfoldingcited by 5
  9. 2023Distortion-Disentangled Contrastive Learningcited by 4
  10. 2023Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisonscited by 4
  11. 2022Differentially Private Federated Combinatorial Bandits with Constraintscited by 3
  12. 2023TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequencescited by 3
  13. 2025InstanceV: Instance-Level Video Generationcited by 3
  14. 2021Stochastic Block-ADMM for Training Deep Networkscited by 2
  15. 2021Exchangeability-Aware Sum-Product Networkscited by 2
  16. 2023Debiasing, calibrating, and improving Semi-supervised Learning performance via simple Ensemble Projectorcited by 2
  17. 2023A hybrid approach for solving the gravitational N-body problem with Artificial Neural Networkscited by 2
  18. 2021A Clustering-based Framework for Classifying Data Streamscited by 1
  19. 2021Shape Modeling with Spline Partitionscited by 1
  20. 2022An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Applicationcited by 1
  21. 2023Robust Learning-Based Incipient Slip Detection using the PapillArray Optical Tactile Sensor for Improved Robotic Grippingcited by 1
  22. 2024Identifying Nonstationary Causal Structures with High-Order Markov Switching Modelscited by 1
  23. 2024Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modelingcited by 1
  24. 2021Optimal Algorithms for Range Searching over Multi-Armed Banditscited by 0
  25. 2021AdaL: Adaptive Gradient Transformation Contributes to Convergences and Generalizationscited by 0
  26. 2025Federated learning over physical channels: adaptive algorithms with near-optimal guaranteescited by 0
  27. 2026FedVG: Gradient-Guided Aggregation for Enhanced Federated Learningcited by 0
  28. 2026Reading Between the Pixels: An Inscriptive Jailbreak Attack on Text-to-Image Modelscited by 0
  29. 2026SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learningcited by 0
  30. 2026Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learningcited by 0
  31. 2026Sequential sparse Gaussian process quantile regressioncited by 0