Benign Overfitting in Out-of-Distribution Generalization of Linear Models | Paper Citation Record

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This paper cites write newline.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models write newline

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This paper cites Importance sampling: Intrinsic dimension and computational cost.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Importance sampling: Intrinsic dimension and computational cost

Reference 2

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This paper cites On robustness of principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On robustness of principal component regression

Reference 3

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This paper cites Determining the number of factors in approximate factor models.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Determining the number of factors in approximate factor models

Reference 5

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This paper cites Prediction by supervised principal components.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Prediction by supervised principal components

Reference 6

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This paper cites Benign overfitting in linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Benign overfitting in linear regression

Reference 7

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This paper cites Deep learning: a statistical viewpoint.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Deep learning: a statistical viewpoint

Reference 8

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This paper cites Laplacian eigenmaps for dimensionality reduction and data representation.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Laplacian eigenmaps for dimensionality reduction and data representation

Reference 9

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This paper cites Two models of double descent for weak features.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Two models of double descent for weak features

Reference 10

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This paper cites Analysis of representations for domain adaptation.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Analysis of representations for domain adaptation

Reference 11

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This paper cites A new look at an old problem: A universal learning approach to linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A new look at an old problem: A universal learning approach to linear regression

Reference 12

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This paper cites Project cost estimation using principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Project cost estimation using principal component regression

Reference 13

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This paper cites High-dimensional kernel methods under covariate shift: Data-dependent implicit regularization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional kernel methods under covariate shift: Data-dependent implicit regularization

Reference 14

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This paper cites Spectral methods for data science: A statistical perspective.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Spectral methods for data science: A statistical perspective

Reference 15

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This paper cites On the robustness of the minimim l2 interpolator.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the robustness of the minimim l2 interpolator

Reference 16

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This paper cites Learning bounds for importance weighting.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Learning bounds for importance weighting

Reference 17

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This paper cites Genetic algorithms applied to the selection of factors in principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Genetic algorithms applied to the selection of factors in principal component regression

Reference 18

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Observation f2c715d5-0bb7-4f38-8e80-9ef8ef699e80 · outbound

This paper cites High-dimensional asymptotics of prediction: Ridge regression and classification.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional asymptotics of prediction: Ridge regression and classification

Reference 19

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This paper cites Factor augmented sparse throughput deep relu neural networks for high dimensional regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Factor augmented sparse throughput deep relu neural networks for high dimensional regression

Reference 20

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This paper cites Factor-adjusted regularized model selection.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Factor-adjusted regularized model selection

Reference 21

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Observation 997d2a57-20c4-43b5-bb8c-90e5d13d3c48 · outbound

This paper cites Robust high dimensional factor models with applications to statistical machine learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Robust high dimensional factor models with applications to statistical machine learning

Reference 22

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This paper cites On the Provable Advantage of Unsupervised Pretraining.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the Provable Advantage of Unsupervised Pretraining

Reference 23

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This paper cites Maximum likelihood estimation is all you need for well-specified covariate shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Maximum likelihood estimation is all you need for well-specified covariate shift

Reference 24

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This paper cites When do neural networks outperform kernel methods? Advances in Neural Information Processing Systems, 33: 0 14820--14830, 2020.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models When do neural networks outperform kernel methods? Advances in Neural Information Processing Systems, 33: 0 14820--14830, 2020

Reference 25

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This paper cites Linearized two-layers neural networks in high dimension.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Linearized two-layers neural networks in high dimension

Reference 26

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This paper cites Domain adaptation for medical image analysis: a survey.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Domain adaptation for medical image analysis: a survey

Reference 27

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This paper cites Some cautionary notes on the use of principal components regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Some cautionary notes on the use of principal components regression

Reference 28

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This paper cites On the value of target data in transfer learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the value of target data in transfer learning

Reference 29

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This paper cites On the Benefits of Over-parameterization for Out-of-Distribution Generalization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the Benefits of Over-parameterization for Out-of-Distribution Generalization

Reference 30

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This paper cites Surprises in high-dimensional ridgeless least squares interpolation.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Surprises in high-dimensional ridgeless least squares interpolation

Reference 31

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This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 32

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This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 33

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This paper cites Alternative principal components regression procedures for dendrohydrologic reconstructions.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Alternative principal components regression procedures for dendrohydrologic reconstructions

Reference 34

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This paper cites Improved principal component regression for face recognition under illumination variations.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Improved principal component regression for face recognition under illumination variations

Reference 35

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This paper cites Investigation of alternative regressions: Some practical examples.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Investigation of alternative regressions: Some practical examples

Reference 36

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This paper cites Two case studies in the application of principal component analysis.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Two case studies in the application of principal component analysis

Reference 37

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This paper cites A note on the use of principal components in regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A note on the use of principal components in regression

Reference 38

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Observation e5aec3bc-dcae-49d6-a9e0-67dc96b966a3 · outbound

This paper cites Double descent and overfitting under noisy inputs and distribution shift for linear denoisers.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Double descent and overfitting under noisy inputs and distribution shift for linear denoisers

Reference 39

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This paper cites Multivariate concentration determination using principal component regression with residual analysis.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Multivariate concentration determination using principal component regression with residual analysis

Reference 40

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This paper cites The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization

Reference 41

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Observation e699ea1c-de78-4a7d-8431-566f76ee8214 · outbound

This paper cites Uniform convergence of interpolators: Gaussian width, norm bounds and benign overfitting.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Uniform convergence of interpolators: Gaussian width, norm bounds and benign overfitting

Reference 42

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This paper cites Wilds: A benchmark of in-the-wild distribution shifts.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Wilds: A benchmark of in-the-wild distribution shifts

Reference 43

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This paper cites Marginal singularity, and the benefits of labels in covariate-shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Marginal singularity, and the benefits of labels in covariate-shift

Reference 44

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This paper cites Forecasting of air quality in delhi using principal component regression technique.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Forecasting of air quality in delhi using principal component regression technique

Reference 45

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Observation 79a4cc3c-a656-4443-9617-b032b046f639 · outbound

This paper cites Near-optimal linear regression under distribution shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Near-optimal linear regression under distribution shift

Reference 46

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This paper cites On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels

Reference 47

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Observation 925a40fa-a122-405e-a7ed-7efaff9c714a · outbound

This paper cites Principal component regression analysis with spss.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression analysis with spss

Reference 48

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Observation 051e1537-b0b4-4738-92b2-28c9a99c99af · outbound

This paper cites Optimally tackling covariate shift in rkhs-based nonparametric regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Optimally tackling covariate shift in rkhs-based nonparametric regression

Reference 49

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This paper cites Minimum-norm interpolation under covariate shift.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Minimum-norm interpolation under covariate shift

Reference 50

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Observation 154dbe28-452e-4145-9133-3b90ac5df0ec · outbound

This paper cites Principal components regression in exploratory statistical research.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal components regression in exploratory statistical research

Reference 51

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Observation 87d3cfc4-5488-45c9-9938-1a0ef9952d1b · outbound

This paper cites The generalization error of random features regression: Precise asymptotics and the double descent curve.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The generalization error of random features regression: Precise asymptotics and the double descent curve

Reference 52

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Observation 54f6bb04-1da3-4f2c-bd90-000023ddb3a0 · outbound

This paper cites Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration

Reference 53

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Observation 8b47450e-38fd-4bdc-aaab-06ec5af6f1cf · outbound

This paper cites Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization

Reference 54

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Observation 5593328a-32c4-4ed4-a876-9e183d8c9c79 · outbound

This paper cites The interpolation phase transition in neural networks: Memorization and generalization under lazy training.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The interpolation phase transition in neural networks: Memorization and generalization under lazy training

Reference 55

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Observation 5f80ba5f-a147-4cd1-a578-b28f98e869bd · outbound

This paper cites Minimax lower bounds for transfer learning with linear and one-hidden layer neural networks.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Minimax lower bounds for transfer learning with linear and one-hidden layer neural networks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.997426Z

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Observation 3e2718f6-0087-4476-bc8d-77a949895b67 · outbound

This paper cites Harmless interpolation of noisy data in regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Harmless interpolation of noisy data in regression

Reference 57

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This paper cites Principal component regression in nir analysis: viewpoints, background details and selection of components.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression in nir analysis: viewpoints, background details and selection of components

Reference 58

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This paper cites More Data Can Hurt for Linear Regression: Sample-wise Double Descent.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models More Data Can Hurt for Linear Regression: Sample-wise Double Descent

Reference 59

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This paper cites In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.971236Z

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Observation 158a172f-4874-473b-9f25-1f42c0e19b79 · outbound

This paper cites Manifold regularization and semi-supervised learning: Some theoretical analyses.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Manifold regularization and semi-supervised learning: Some theoretical analyses

Reference 61

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This paper cites A new similarity measure for covariate shift with applications to nonparametric regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A new similarity measure for covariate shift with applications to nonparametric regression

Reference 62

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Observation 836c816b-9a0b-4c12-ae82-2d60e4647abb · outbound

This paper cites Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389--5400.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389--5400

Reference 63

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This paper cites Asymptotics of ridge (less) regression under general source condition.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Asymptotics of ridge (less) regression under general source condition

Reference 64

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This paper cites The implicit bias of benign overfitting.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models The implicit bias of benign overfitting

Reference 65

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Observation 339ef73d-6dcb-4d6d-9dda-54d3abb801d3 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Improving predictive inference under covariate shift by weighting the log-likelihood function

Reference 66

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This paper cites More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory

Reference 67

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This paper cites Forecasting using principal components from a large number of predictors.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Forecasting using principal components from a large number of predictors

Reference 68

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Observation 2d119888-04cd-4102-af42-8b1ec0f08d4f · outbound

This paper cites A correlation principal component regression analysis of nir data.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A correlation principal component regression analysis of nir data

Reference 69

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Observation aa23c5e3-1d37-474f-9c8f-bb324b9caf91 · outbound

This paper cites Overparameterization improves robustness to covariate shift in high dimensions.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Overparameterization improves robustness to covariate shift in high dimensions

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.889724Z

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Observation 6abe1e79-416d-48eb-9f0a-8a8970ffba2d · outbound

This paper cites Provable meta-learning of linear representations.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Provable meta-learning of linear representations

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.877819Z

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Observation 54c5f259-0a3a-45c7-afc7-cae5536eb493 · outbound

This paper cites Bartlett.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Bartlett

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.865578Z

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This paper cites An inequality for trace ideals.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models An inequality for trace ideals

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.854803Z

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Observation eb5848fe-8a41-466a-8792-fd385fd97a34 · outbound

This paper cites Introduction to the non-asymptotic analysis of random matrices.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Introduction to the non-asymptotic analysis of random matrices

Reference 74

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Observation a794e6c6-cdd8-49b5-960e-fe3b8977b800 · outbound

This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models High-dimensional probability: An introduction with applications in data science, volume 47

Reference 75

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This paper cites Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.837206Z

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Observation 42753bd3-d427-49aa-b4e1-541dc6e8b7ba · outbound

This paper cites Perturbation theory for pseudo-inverses.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Perturbation theory for pseudo-inverses

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.825058Z

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Observation 35dd1de1-6760-4b12-b91c-73968b8d4ee7 · outbound

This paper cites Assaying out-of-distribution generalization in transfer learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Assaying out-of-distribution generalization in transfer learning

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.815177Z

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Observation f23e386e-c779-487c-a364-be49753a6681 · outbound

This paper cites On the optimal weighted l2 regularization in overparameterized linear regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the optimal weighted l2 regularization in overparameterized linear regression

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.805315Z

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Observation 73e6a05a-6ba5-452f-bac9-2b81027ddc8e · outbound

This paper cites On the number of variables to use in principal component regression.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On the number of variables to use in principal component regression

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.795362Z

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Observation 339644f8-2bff-47a2-8f3a-72da10ac2083 · outbound

This paper cites Understanding Why Generalized Reweighting Does Not Improve Over ERM.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Understanding Why Generalized Reweighting Does Not Improve Over ERM

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:16.608454Z

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This paper cites A class of geometric structures in transfer learning: Minimax bounds and optimality.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models A class of geometric structures in transfer learning: Minimax bounds and optimality

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:16.612296Z

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Observation aa7be798-e666-483d-87e0-85ced2b635d1 · outbound

This paper cites On uniform convergence and low-norm interpolation learning.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On uniform convergence and low-norm interpolation learning

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.778390Z

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Observation 3aa1f6eb-d3f1-4776-aac0-d82fcffa0618 · outbound

This paper cites Unsupervised domain adaptation for semantic segmentation via class-balanced self-training.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models Unsupervised domain adaptation for semantic segmentation via class-balanced self-training

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:16.767662Z

Source-reported events for the cited work

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Observation bcb72342-93fa-4be0-a13e-e5bb548ae964 · outbound

This paper cites @esa (Ref.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models @esa (Ref

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:16.623327Z

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Observation 90a5cbd8-46ab-45dd-9467-8644548e264e · outbound

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Benign Overfitting in Out-of-Distribution Generalization of Linear Models Unresolved cited work

Reference 86

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Observation bb60194a-e6e4-435c-a0f6-1213d6e74928 · outbound

This paper cites On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:16.630215Z

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