{"total":15,"rows":[{"id":"2109.09859","title":"Sharp global convergence guarantees for iterative nonconvex optimization: A Gaussian process perspective","created":"2021-09-20","cited_by_count":10,"area":null},{"id":"2205.13166","title":"On Learning Mixture of Linear Regressions in the Non-Realizable Setting","created":"2022-05-26","cited_by_count":10,"area":null},{"id":"2107.03455","title":"Model Selection for Generic Contextual Bandits","created":"2021-07-07","cited_by_count":8,"area":null},{"id":"2205.03246","title":"What Makes A Good Fisherman? Linear Regression under Self-Selection Bias","created":"2022-05-06","cited_by_count":7,"area":null},{"id":"2212.01314","title":"On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds","created":"2022-12-02","cited_by_count":6,"area":null},{"id":"2111.01348","title":"Faster Algorithms for Learning Convex Functions","created":"2021-11-02","cited_by_count":5,"area":null},{"id":"2505.21208","title":"Input Convex Kolmogorov Arnold Networks","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2102.12066","title":"On the Minimal Error of Empirical Risk Minimization","created":"2021-02-24","cited_by_count":3,"area":null},{"id":"2308.08070","title":"Max-affine regression via first-order methods","created":"2023-08-15","cited_by_count":3,"area":null},{"id":"2103.07020","title":"Max-Linear Regression by Convex Programming","created":"2021-03-12","cited_by_count":2,"area":null},{"id":"2107.05849","title":"Model Selection for Generic Reinforcement Learning","created":"2021-07-13","cited_by_count":1,"area":null},{"id":"2207.02992","title":"Model Selection in Reinforcement Learning with General Function Approximations","created":"2022-07-06","cited_by_count":1,"area":null},{"id":"2406.01149","title":"Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms","created":"2024-06-03","cited_by_count":1,"area":null},{"id":"2604.05842","title":"Expectation Maximization (EM) Converges for General Agnostic Mixtures","created":"2026-04-07","cited_by_count":0,"area":null},{"id":"2605.06959","title":"Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions","created":"2026-05-07","cited_by_count":0,"area":null}],"next_cursor":null}