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minimax optimal rate

38 papers

Papers

A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation JMLR 2026 Nonparametric Estimation of a Factorizable Density using Diffusion Models JMLR 2026 Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention ALT 2026 Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal ICML 2025 Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity ICML 2025 On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension JMLR 2025 Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression ICLR 2025 Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights JMLR 2025 Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees ICLR 2025 Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design JMLR 2024 Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024 Non-parametric classification via expand-and-sparsify representation NeurIPS 2024 Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks JMLR 2024 On The Statistical Complexity of Offline Decision-Making ICML 2024 Statistical Spatially Inhomogeneous Diffusion Inference AAAI 2024 Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes ICML 2024 The Aggregation–Heterogeneity Trade-off in Federated Learning COLT 2023 The Exact Sample Complexity Gain from Invariances for Kernel Regression NeurIPS 2023 Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models JMLR 2023 A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation ICML 2022 A NON-PARAMETRIC REGRESSION VIEWPOINT : GENERALIZATION OF OVERPARAMETRIZED DEEP RELU NETWORK UNDER NOISY OBSERVATIONS ICLR 2022 Asymptotic Properties for Bayesian Neural Network in Besov Space NeurIPS 2022 On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation ICML 2022 Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism NeurIPS 2021 Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021