minimax lower bound

A Complexity Measure for Active Learning in Multi-group Mean Estimation COLT 2026 Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions COLT 2026 Provably Efficient Reinforcement Learning in Continuous-Time Episodic MDPs with Poisson Decision Epochs UAI 2026 Statistical guarantees for denoising reflected diffusion models JMLR 2026 Wasserstein Policy Learning for Distributional Outcomes COLT 2026 Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift ICLR 2025 Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization AISTATS 2025 Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model AISTATS 2025 Transfer Learning for Nonparametric Contextual Dynamic Pricing ICML 2025 Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures NeurIPS 2024 Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability NeurIPS 2024 Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design JMLR 2024 Fixed-Budget Differentially Private Best Arm Identification ICLR 2024 Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm JMLR 2024 Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024 Lost Domain Generalization Is a Natural Consequence of Lack of Training Domains AAAI 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms NeurIPS 2024 On the Saturation Effects of Spectral Algorithms in Large Dimensions NeurIPS 2024 On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity NeurIPS 2024 Optimal score estimation via empirical Bayes smoothing COLT 2024 Prediction from compression for models with infinite memory, with applications to hidden Markov and renewal processes COLT 2024 Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions NeurIPS 2024 Smoothness Adaptive Hypothesis Transfer Learning ICML 2024 Statistical curriculum learning: An elimination algorithm achieving an oracle risk COLT 2024 Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024