Nonparametric Estimation of a Factorizable Density using Diffusion Models

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Learning Bayesian Network Classifiers to Minimize Class Variable Parameters

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Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation

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An Anytime Algorithm for Good Arm Identification

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Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification

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Neural Network Parameter-optimization of Gaussian Pre-marginalized Directed Acyclic Graphs

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Flexible Functional Treatment Effect Estimation

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Error Analysis for Deep ReLU Feedforward Density-Ratio Estimation with Bregman Divergence

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A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design

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UQLM: A Python Package for Uncertainty Quantification in Large Language Models

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Nonlinear function-on-function regression by RKHS

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Nonlocal Techniques for the Analysis of Deep ReLU Neural Network Approximations

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A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation

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Guaranteed Nonconvex Low-Rank Tensor Estimation via Scaled Gradient Descent

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skwdro: a library for Wasserstein distributionally robust machine learning

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Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation

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Stochastic Gradient Methods: Bias, Stability and Generalization

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Classification Under Local Differential Privacy with Model Reversal and Model Averaging

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Identifying Weight-Variant Latent Causal Models

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Efficient frequent directions algorithms for approximate decomposition of matrices and higher-order tensors

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