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Jeffrey Negrea

Concept algebra for (score-based) text-controlled generative models
Concept Algebra for Text-Controlled Vision Models
Relaxing the i.i.d. assumption: Adaptively minimax optimal regret via root-entropic regularization
Approximations of Geometrically Ergodic Reversible Markov Chains
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers
Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors
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