{"total":22,"rows":[{"id":"2109.08844","title":"Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks","created":"2021-09-18","cited_by_count":41,"area":null},{"id":"2408.12186","title":"Transformers are Minimax Optimal Nonparametric In-Context Learners","created":"2024-08-22","cited_by_count":37,"area":null},{"id":"2305.18699","title":"Approximation and Estimation Ability of Transformers for Sequence-to-Sequence Functions with Infinite Dimensional Input","created":"2023-05-30","cited_by_count":32,"area":null},{"id":"2302.05933","title":"Generalization Ability of Wide Neural Networks on $\\mathbb{R}$","created":"2023-02-12","cited_by_count":30,"area":null},{"id":"2401.07187","title":"A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models","created":"2024-01-14","cited_by_count":20,"area":null},{"id":"2301.09517","title":"Sampling-based Nystr\\\"om Approximation and Kernel Quadrature","created":"2023-01-23","cited_by_count":17,"area":null},{"id":"2403.14917","title":"Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective","created":"2024-03-22","cited_by_count":13,"area":null},{"id":"2207.02546","title":"Adaptive deep learning for nonlinear time series models","created":"2022-07-06","cited_by_count":11,"area":null},{"id":"2205.07764","title":"On the inability of Gaussian process regression to optimally learn compositional functions","created":"2022-05-16","cited_by_count":7,"area":null},{"id":"2405.01304","title":"Misclassification bounds for PAC-Bayesian sparse deep learning","created":"2024-05-02","cited_by_count":7,"area":null},{"id":"2301.11936","title":"Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation","created":"2023-01-27","cited_by_count":5,"area":null},{"id":"2405.16696","title":"How many samples are needed to train a deep neural network?","created":"2024-05-26","cited_by_count":5,"area":null},{"id":"2406.08321","title":"Deep learning from strongly mixing observations: Sparse-penalized regularization and minimax optimality","created":"2024-06-12","cited_by_count":3,"area":null},{"id":"2501.04898","title":"Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression","created":"2025-01-09","cited_by_count":3,"area":null},{"id":"2502.11467","title":"Approximation of Permutation Invariant Polynomials by Transformers: Efficient Construction in Column-Size","created":"2025-02-17","cited_by_count":3,"area":null},{"id":"2606.06368","title":"Optimally taming biases in black-box models for efficient semiparametric estimation","created":"2026-06-04","cited_by_count":3,"area":null},{"id":"2106.04795","title":"Nonasymptotic theory for two-layer neural networks: Beyond the bias-variance trade-off","created":"2021-06-09","cited_by_count":2,"area":null},{"id":"2304.08172","title":"Pointwise convergence of Fourier series and deep neural network for the indicator function of d-dimensional ball","created":"2023-04-17","cited_by_count":0,"area":null},{"id":"2510.23197","title":"Model-free filtering in high dimensions via projection and score-based diffusions","created":"2025-10-27","cited_by_count":0,"area":null},{"id":"2602.04233","title":"Provable Target Sample Complexity Improvements as Pre-Trained Models Scale","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2603.23302","title":"A Theory of Nonparametric Covariance Function Estimation for Discretely Observed Data","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2606.02008","title":"Provable Data Scaling Law for Meta Learning via Complexity Minimization","created":"2026-06-01","cited_by_count":0,"area":null}],"next_cursor":null}