{"total":13,"rows":[{"id":"2405.00592","title":"Scaling and renormalization in high-dimensional regression","created":"2024-05-01","cited_by_count":50,"area":null},{"id":"2405.15699","title":"Dimension-free deterministic equivalents and scaling laws for random feature regression","created":"2024-05-24","cited_by_count":23,"area":null},{"id":"2410.18938","title":"A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities","created":"2024-10-24","cited_by_count":16,"area":null},{"id":"2409.13904","title":"High-dimensional learning of narrow neural networks","created":"2024-09-20","cited_by_count":12,"area":null},{"id":"2505.03577","title":"Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime","created":"2025-05-06","cited_by_count":6,"area":null},{"id":"2410.16073","title":"On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds","created":"2024-10-21","cited_by_count":4,"area":null},{"id":"2603.14578","title":"Power-Law Spectrum of the Random Feature Model","created":"2026-03-15","cited_by_count":4,"area":null},{"id":"2507.07907","title":"A statistical physics framework for optimal learning","created":"2025-07-10","cited_by_count":3,"area":null},{"id":"2506.12454","title":"On the Existence of Consistent Adversarial Attacks in High-Dimensional Linear Classification","created":"2025-06-14","cited_by_count":2,"area":null},{"id":"2510.16250","title":"One-Bit Quantization for Random Features Models","created":"2025-10-17","cited_by_count":0,"area":null},{"id":"2512.10407","title":"Supervised Learning of Random Neural Architectures Structured by Latent Random Fields on Compact Boundaryless Multiply-Connected Manifolds","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2601.23208","title":"A Random Matrix Theory of Masked Self-Supervised Regression","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2605.10290","title":"Characterizing the Generalization Error of Random Feature Regression with Arbitrary Data-Augmentation","created":"2026-05-11","cited_by_count":0,"area":null}],"next_cursor":null}