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arXiv · 2508.21396

PMODE: Theoretically Grounded and Modular Mixture Modeling

Robert A. Vandermeulen
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Abstract

We introduce PMODE (Partitioned Mixture Of Density Estimators), a general and modular framework for mixture modeling with both parametric and nonparametric components. PMODE builds mixtures by partitioning the data and fitting separate estimators to each subset. It attains near-optimal rates for this estimator class and remains valid even when the mixture components come from different distribution families. As an application, we develop MV-PMODE, which scales a previously theoretical approach to high-dimensional density estimation to settings with thousands of dimensions. Despite its simplicity, it performs competitively against deep baselines on CIFAR-10 anomaly detection.

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Robert A. Vandermeulen. 2025-08-29. PMODE: Theoretically Grounded and Modular Mixture Modeling. https://arxiv.org/abs/2508.21396

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