minimax optimality

High-dimensional Parameter Transfer With Fused-Regularizer JMLR 2026 Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes JMLR 2026 On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits COLT 2026 When Does Model Multiplicity Affect Prediction Intervals? A Sharp Phase Transition UAI 2026 Generalized multi-view model: Adaptive density estimation under low-rank constraints JMLR 2025 Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness JMLR 2025 Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary JMLR 2025 Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps UAI 2025 Minimax Optimal Two-Sample Testing under Local Differential Privacy JMLR 2025 On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality ICLR 2025 Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions JMLR 2025 Self-Improvement in Language Models: The Sharpening Mechanism ICLR 2025 Signal Recovery from Random Dot-Product Graphs under Local Differential Privacy AISTATS 2025 Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees ICML 2025 Adaptivity of Diffusion Models to Manifold Structures AISTATS 2024 Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift ICLR 2024 Minimax Linear Regression under the Quantile Risk COLT 2024 Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods ICLR 2024 Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions ICML 2024 Minimax-optimal reward-agnostic exploration in reinforcement learning COLT 2024 Minimax Rates for High-Dimensional Random Tessellation Forests JMLR 2024 Non-parametric classification via expand-and-sparsify representation NeurIPS 2024 On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains JMLR 2024 On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives JMLR 2024 Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024