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Nonparametric Estimation of a Factorizable Density using Diffusion Models
Published in Journal of Machine Learning Research (2026)“…Journal Article…”
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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
Published in Journal of Machine Learning Research (2026)“…Journal Article…”
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