{"total":19,"rows":[{"id":"2405.00592","title":"Scaling and renormalization in high-dimensional regression","created":"2024-05-01","cited_by_count":50,"area":null},{"id":"2302.00375","title":"Bayes-optimal Learning of Deep Random Networks of Extensive-width","created":"2023-02-01","cited_by_count":41,"area":null},{"id":"2302.00401","title":"Deterministic equivalent and error universality of deep random features learning","created":"2023-02-01","cited_by_count":35,"area":null},{"id":"2403.08160","title":"Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime","created":"2024-03-13","cited_by_count":26,"area":null},{"id":"2205.14846","title":"Precise Learning Curves and Higher-Order Scaling Limits for Dot Product Kernel Regression","created":"2022-05-30","cited_by_count":22,"area":null},{"id":"2308.13431","title":"Six Lectures on Linearized Neural Networks","created":"2023-08-25","cited_by_count":20,"area":null},{"id":"2401.01270","title":"Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions","created":"2024-01-02","cited_by_count":11,"area":null},{"id":"2404.12597","title":"The phase diagram of kernel interpolation in large dimensions","created":"2024-04-19","cited_by_count":9,"area":null},{"id":"2211.06077","title":"Overparameterized random feature regression with nearly orthogonal data","created":"2022-11-11","cited_by_count":7,"area":null},{"id":"2402.10164","title":"Random features and polynomial rules","created":"2024-02-15","cited_by_count":6,"area":null},{"id":"2212.06757","title":"Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures","created":"2022-12-13","cited_by_count":5,"area":null},{"id":"2511.03892","title":"A general technique for approximating high-dimensional empirical kernel matrices","created":"2025-11-05","cited_by_count":4,"area":null},{"id":"2312.14922","title":"Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks","created":"2023-12-22","cited_by_count":3,"area":null},{"id":"2409.00915","title":"On the Pinsker bound of inner product kernel regression in large dimensions","created":"2024-09-02","cited_by_count":2,"area":null},{"id":"2503.00504","title":"On the Saturation Effects of Spectral Algorithms in Large Dimensions","created":"2025-03-01","cited_by_count":2,"area":null},{"id":"2306.03783","title":"Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression","created":"2023-06-06","cited_by_count":1,"area":null},{"id":"2311.11093","title":"Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem","created":"2023-11-18","cited_by_count":1,"area":null},{"id":"2412.18756","title":"Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories","created":"2024-12-25","cited_by_count":0,"area":null},{"id":"2604.23212","title":"Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions","created":"2026-04-25","cited_by_count":0,"area":null}],"next_cursor":null}