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Jeffrey Negrea

Approximations of Geometrically Ergodic Reversible Markov Chains
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers
Statistical Inference with Stochastic Gradient Algorithms
Statistical Inference with Stochastic Gradient Algorithms
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors
Relaxing the IID Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization
Relaxing the IID Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-IID Targets
Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-IID Targets

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