Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization | Paper Citation Record

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This paper cites Systematic generalisation with group invariant predictions.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Systematic generalisation with group invariant predictions

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.316953Z

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This paper cites Invariant Risk Minimization.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Invariant Risk Minimization

Reference 2

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Observation a7995196-6fe3-4fb6-bd54-b4fde7eaf760 · outbound

This paper cites High-dimensional asymptotics of feature learning: How one gradient step improves the representation.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization High-dimensional asymptotics of feature learning: How one gradient step improves the representation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.301291Z

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This paper cites Deep learning: a statistical viewpoint.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Deep learning: a statistical viewpoint

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.284905Z

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This paper cites Reconciling modern machine-learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Reconciling modern machine-learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019

Reference 5

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This paper cites Memorization and optimization in deep neural networks with minimum over-parameterization.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Memorization and optimization in deep neural networks with minimum over-parameterization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.258895Z

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Observation 3630a444-cdea-47b3-96e6-1726c9cd5749 · outbound

This paper cites Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.190463Z

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This paper cites Privacy for Free in the Overparameterized Regime.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Privacy for Free in the Overparameterized Regime

Reference 8

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This paper cites A universal law of robustness via isoperimetry.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization A universal law of robustness via isoperimetry

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:32.092617Z

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Observation 2376d210-4b8f-4eda-a1de-b5edd8794124 · outbound

This paper cites Chang, G.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Chang, G

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.970971Z

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Observation c24d0ef4-abf7-4d8e-9903-ef1717d3809f · outbound

This paper cites Provable benefits of overparameterization in model compression: From double descent to pruning neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Provable benefits of overparameterization in model compression: From double descent to pruning neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.954495Z

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Observation 60290383-7d32-474a-9c6e-34b21ae7b44d · outbound

This paper cites Dimension free ridge regression.The Annals of Statistics, 52(6):2879 – 2912, 2024.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Dimension free ridge regression.The Annals of Statistics, 52(6):2879 – 2912, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.928922Z

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Observation 5d423cdc-b8bf-41fc-9e5d-445f2f61a508 · outbound

This paper cites Neural networks can learn representations with gradient descent.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Neural networks can learn representations with gradient descent

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.902502Z

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Observation a8a546d0-e760-4256-ae10-a79208e2cba8 · outbound

This paper cites On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes

Reference 14

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Observation 55642ab9-5e5d-4e69-ba0c-120764d1cf5c · outbound

This paper cites Wichmann.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Wichmann

Reference 15

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Observation 6c327376-df14-46e1-bd93-6b9f33b10920 · outbound

This paper cites Wichmann, and Wieland Brendel.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Wichmann, and Wieland Brendel

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.876936Z

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Observation f632a93e-c739-40fe-9028-a51972fdad9c · outbound

This paper cites The gaussian equivalence of generative models for learning with shallow neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The gaussian equivalence of generative models for learning with shallow neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.861515Z

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Observation e091a4c2-0f22-41ef-86b3-d7abfc2fe278 · outbound

This paper cites Modeling the influence of data structure on learning in neural networks: The hidden manifold model.Physical Review X, 10(4):041044, 2020.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Modeling the influence of data structure on learning in neural networks: The hidden manifold model.Physical Review X, 10(4):041044, 2020

Reference 18

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Observation 37068ab9-fe1b-4c77-b5d0-ac4e0e7cc98d · outbound

This paper cites The distribution of ridgeless least squares interpolators.arXiv preprint arXiv:2307.02044, 2023.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The distribution of ridgeless least squares interpolators.arXiv preprint arXiv:2307.02044, 2023

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.377932Z

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Observation ca6a6485-53e2-45ae-9d84-536d04f17766 · outbound

This paper cites The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression.The Annals of Statistics, 52(2):441 – 465, 2024.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression.The Annals of Statistics, 52(2):441 – 465, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.836993Z

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Observation 95407e10-2abc-4eb2-bab0-a74b79748cb6 · outbound

This paper cites Hastie, Andrea Montanari, Saharon Rosset, and Ryan J.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Hastie, Andrea Montanari, Saharon Rosset, and Ryan J

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.821379Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7f6fb99a-5510-4590-823e-0dacb48da18c · outbound

This paper cites What shapes feature representations? Exploring datasets, architectures, and training.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization What shapes feature representations? Exploring datasets, architectures, and training

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.805799Z

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Observation 75b92543-6737-443c-bb77-5faa1b38bc5d · outbound

This paper cites On the foundations of shortcut learning.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization On the foundations of shortcut learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.790233Z

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This paper cites an unresolved cited work.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Unresolved cited work

Reference 24

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Observation a1a92ab5-3e3a-4605-813d-e2a1659f4bfa · outbound

This paper cites On feature learning in the presence of spurious correlations.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization On feature learning in the presence of spurious correlations

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.765792Z

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Observation 05ee59b9-8771-49df-8bdd-66e599b20e02 · outbound

This paper cites Sgd on neural networks learns functions of increasing complexity.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Sgd on neural networks learns functions of increasing complexity

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.750385Z

Source-reported events for the cited work

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Observation e0e8b0d2-29c7-4d83-9c01-8d57211dd602 · outbound

This paper cites Last layer re-training is sufficient for ro- bustness to spurious correlations.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Last layer re-training is sufficient for ro- bustness to spurious correlations

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.734853Z

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Observation eda4bb10-2186-409b-8dc3-fb2659fb2c69 · outbound

This paper cites Demystifying disagreement-on-the-line in high dimensions.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Demystifying disagreement-on-the-line in high dimensions

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.720098Z

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Observation cb14d96d-49d5-487f-96b8-f800cc0d4a00 · outbound

This paper cites Just train twice: Improving group robustness without training group information.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Just train twice: Improving group robustness without training group information

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.704307Z

Source-reported events for the cited work

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Observation abc2ae63-e2f0-4743-b387-6bc31f073cb1 · outbound

This paper cites Avoiding spurious correlations via logit correction.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Avoiding spurious correlations via logit correction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.685433Z

Source-reported events for the cited work

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Observation 9c2553f4-568e-4bda-bfb5-10f5663d0d4a · outbound

This paper cites Learning curves of generic features maps for realistic datasets with a teacher-student model.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Learning curves of generic features maps for realistic datasets with a teacher-student model

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.669389Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6579aa41-dacd-40a0-8c14-304dfd7cc165 · outbound

This paper cites Minimum-norm interpolation under covariate shift.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Minimum-norm interpolation under covariate shift

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.654469Z

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Observation 1ddf58d4-bfa5-4e11-8e1d-b9242f24b7e0 · outbound

This paper cites Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration.Applied and Computational Harmonic Analysis, 59:3–84, 2022.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration.Applied and Computational Harmonic Analysis, 59:3–84, 2022

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.639175Z

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Observation b04f7f3b-00a0-402b-9bde-560d6e8ca0fa · outbound

This paper cites The generalization error of random features regression: Precise asymptotics and the double descent curve.Communications on Pure and Applied Mathematics, 75(4):667– 766, 2022.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The generalization error of random features regression: Precise asymptotics and the double descent curve.Communications on Pure and Applied Mathematics, 75(4):667– 766, 2022

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.624063Z

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Observation 20a5008b-db31-40df-af4a-632015a2245e · outbound

This paper cites Hard imagenet: Segmentations for objects with strong spurious cues.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Hard imagenet: Segmentations for objects with strong spurious cues

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.608530Z

Source-reported events for the cited work

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Observation 2a3ca3f0-6f7d-4220-b681-5c4c074e68e1 · outbound

This paper cites A theory of non-linear feature learning with one gradient step in two-layer neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization A theory of non-linear feature learning with one gradient step in two-layer neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.592785Z

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Observation d007c2da-88e4-4a14-829d-2f82c34bb6b2 · outbound

This paper cites The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime

Reference 37

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Observation 418a0504-5246-481c-b634-babd79c8b861 · outbound

This paper cites Universality of empirical risk minimization.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Universality of empirical risk minimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.577422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a5f0571-8574-489d-b570-5ba62cd5eef3 · outbound

This paper cites Simplicity bias in 1-hidden layer neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Simplicity bias in 1-hidden layer neural networks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.562483Z

Source-reported events for the cited work

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Observation fab760b7-5416-48b3-baaa-0bad2bac01ae · outbound

This paper cites Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.546584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d4152023-78f1-4dac-9f9f-357a37ee31ca · outbound

This paper cites Analysis of Boolean Functions.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Analysis of Boolean Functions

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.529683Z

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Observation bf6a3a26-59e5-4c1f-9d1c-cccab56c7d18 · outbound

This paper cites Gradient starvation: A learning proclivity in neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Gradient starvation: A learning proclivity in neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.514071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 45f53c0a-9c9c-40b7-9a46-0f3d16565daf · outbound

This paper cites Finding and fixing spurious patterns with explanations.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Finding and fixing spurious patterns with explanations

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.497998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 05b5606e-565b-41a1-ba66-4fdea70ca1c6 · outbound

This paper cites Complexity matters: Dynamics of feature learning in the presence of spurious correlations.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Complexity matters: Dynamics of feature learning in the presence of spurious correlations

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.481575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f9c0b59-26bd-4e45-b72a-0af5973842a7 · outbound

This paper cites On the spectral bias of neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization On the spectral bias of neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.465430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abd4bbbd-3b24-49c5-97b6-d093fe5e2bf4 · outbound

This paper cites Random features for large-scale kernel machines.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Random features for large-scale kernel machines

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.508719Z

Source-reported events for the cited work

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Observation 38dc703e-f29e-4a68-befd-4c5803ae26a8 · outbound

This paper cites Early stopping and non-parametric regression: an optimal data-dependent stopping rule.The Journal of Machine Learning Research, 15(1):335–366, 2014.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Early stopping and non-parametric regression: an optimal data-dependent stopping rule.The Journal of Machine Learning Research, 15(1):335–366, 2014

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.513423Z

Source-reported events for the cited work

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Observation 3c70ec90-4188-4895-ac2e-1b1158cdc08b · outbound

This paper cites Hashimoto, and Percy Liang.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Hashimoto, and Percy Liang

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.518196Z

Source-reported events for the cited work

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Observation 32c078ed-6e0e-4511-8f5d-9824298c6de0 · outbound

This paper cites An investigation of why overpa- rameterization exacerbates spurious correlations.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization An investigation of why overpa- rameterization exacerbates spurious correlations

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.416798Z

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Observation 687980b3-12aa-4f26-91f9-e2d1d7745f6f · outbound

This paper cites Information-theoretic bias reduction via causal view of spurious correlation.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Information-theoretic bias reduction via causal view of spurious correlation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.400756Z

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Observation 31276436-ac0b-4cec-ac14-e46bbd661237 · outbound

This paper cites The pitfalls of simplicity bias in neural networks.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization The pitfalls of simplicity bias in neural networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.385396Z

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Observation 4a5562e1-2f0c-40a0-a422-1d2d26bdbfec · outbound

This paper cites Salient imagenet: How to discover spurious features in deep learning? In International Conference on Learning Representations, 2022.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Salient imagenet: How to discover spurious features in deep learning? In International Conference on Learning Representations, 2022

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.370197Z

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Observation 595463b1-cc7c-4074-8bd9-76da87c4a5e3 · outbound

This paper cites Generalization error of min-norm interpolators in transfer learning.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Generalization error of min-norm interpolators in transfer learning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.542667Z

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Observation 852011dd-2f5f-4fbf-809b-f960a06a0f37 · outbound

This paper cites Regularized linear regression: A precise analysis of the estimation error.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Regularized linear regression: A precise analysis of the estimation error

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.354510Z

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Observation a2bf2751-3b4f-4f2b-9e2e-d924399b7a0d · outbound

This paper cites Overcoming simplicity bias in deep networks using a feature sieve.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Overcoming simplicity bias in deep networks using a feature sieve

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.336872Z

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Observation 11dcb660-8231-4679-a47a-5b0619a9142e · outbound

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

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Overparameterization improves robustness to covariate shift in high dimensions

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.318816Z

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Observation e9795b80-9abe-44ce-93b4-e3d2e0403983 · outbound

This paper cites Counterfactual invariance to spurious correlations in text classification.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Counterfactual invariance to spurious correlations in text classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.302107Z

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Observation d6ed948f-ff06-464b-813a-7a6b460ad1fb · outbound

This paper cites Introduction to the non-asymptotic analysis of random matrices, page 210–268.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Introduction to the non-asymptotic analysis of random matrices, page 210–268

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.285426Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7115f763-0a1b-47a6-9ceb-15af64b80555 · outbound

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

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization High-dimensional probability: An introduction with applications in data science

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.268571Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 38d8fefc-1ee5-4da6-a1c8-05717e2fd321 · outbound

This paper cites Noise or signal: The role of image backgrounds in object recognition.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Noise or signal: The role of image backgrounds in object recognition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.250934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39e869ca-e0c4-4319-9646-57195742ba02 · outbound

This paper cites Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.582715Z

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Observation f24aeb67-7553-4b2b-8b74-9fc240f3e07c · outbound

This paper cites Spurious correlations in machine learning: A survey.arXiv preprint arXiv:2402.12715, 2024.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Spurious correlations in machine learning: A survey.arXiv preprint arXiv:2402.12715, 2024

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.587883Z

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Observation e0eb20a4-2449-4849-9429-05bbbf6a8bb5 · outbound

This paper cites Coping with label shift via distributionally robust optimisation.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Coping with label shift via distributionally robust optimisation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-09T15:42:30.592669Z

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Observation a4970b69-33ee-48c3-8fa8-87b15b67fa56 · outbound

This paper cites Examining and combating spurious features under distribution shift.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Examining and combating spurious features under distribution shift

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.223791Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9caa4f4e-5fa3-472b-b90c-5c0c14dc3ed3 · outbound

This paper cites On the relation between accuracy and fairness in binary classification.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization On the relation between accuracy and fairness in binary classification

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:42:31.207379Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf700bda-1201-4b63-87f7-ae07cb5b121f · outbound

This paper cites an unresolved cited work.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:42:31.190540Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6210e68d-c3be-420c-97fc-f8c518566d7f · outbound

This paper cites orthogonal features.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization orthogonal features

Reference 67

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T15:42:31.173480Z

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