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minimax optimality

76 papers

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Co-occurring keywords

minimax optimal (89) sample complexity (1158) convergence rate (606) kernel ridge regression (111) hypothesis testing (254) reproducing kernel hilbert space (334) regret bound (1918) density estimation (397) multi-armed bandit (1091) bayesian inference (1904)

Papers

Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness JMLR 2025
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions JMLR 2025
Generalized multi-view model: Adaptive density estimation under low-rank constraints JMLR 2025
Minimax Optimal Two-Sample Testing under Local Differential Privacy JMLR 2025
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary JMLR 2025
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NIPS 2024
Minimax Rates for High-Dimensional Random Tessellation Forests JMLR 2024
Adaptivity of Diffusion Models to Manifold Structures AISTATS 2024
Minimax-optimal reward-agnostic exploration in reinforcement learning COLT 2024
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains JMLR 2024
Structured Optimal Variational Inference for Dynamic Latent Space Models JMLR 2024
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality JMLR 2024
Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024
Optimistic Search: Change Point Estimation for Large-scale Data via Adaptive Logarithmic Queries JMLR 2024
On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives JMLR 2024
Rates of convergence for density estimation with generative adversarial networks JMLR 2024
Non-parametric classification via expand-and-sparsify representation NIPS 2024
Minimax Linear Regression under the Quantile Risk COLT 2024
Learning Functional Distributions with Private Labels ICML 2023
The Art of BART: Minimax Optimality over Nonhomogeneous Smoothness in High Dimension JMLR 2023
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators JMLR 2023
Thompson Sampling with Less Exploration is Fast and Optimal ICML 2023
Minimax Nonparametric Two-Sample Test under Adversarial Losses AISTATS 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023