# The fused Kolmogorov filter: A nonparametric model-free screening method

arXiv: https://arxiv.org/abs/1403.7701 · HTML: https://mlsanity.com/paper/1403.7701/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2014.

## Built on by (most cited first, 7 of 7)

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- [A model-free feature selection technique of feature screening and random forest based recursive feature elimination](https://mlsanity.com/paper/2302.07449/) (2023)
- [RaSE: A Variable Screening Framework via Random Subspace Ensembles](https://mlsanity.com/paper/2102.03892/) (2021)
- [Feature space reduction method for ultrahigh-dimensional, multiclass data: Random forest-based multiround screening (RFMS)](https://mlsanity.com/paper/2305.15793/) (2023)
- [Sparse minimum Redundancy Maximum Relevance for feature selection](https://mlsanity.com/paper/2508.18901/) (2025)
- [Cluster-Based Dimensionality Reduction by Nonparametric Distributional Screening](https://mlsanity.com/paper/2609.06854/) (2026)
- [PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models](https://mlsanity.com/paper/2609.23574/) (2026)

## Abstract (arXiv)

A new model-free screening method called the fused Kolmogorov filter is proposed for high-dimensional data analysis. This new method is fully nonparametric and can work with many types of covariates and response variables, including continuous, discrete and categorical variables. We apply the fused Kolmogorov filter to deal with variable screening problems emerging from a wide range of applications, such as multiclass classification, nonparametric regression and Poisson regression, among others. It is shown that the fused Kolmogorov filter enjoys the sure screening property under weak regularity conditions that are much milder than those required for many existing nonparametric screening methods. In particular, the fused Kolmogorov filter can still be powerful when covariates are strongly dependent on each other. We further demonstrate the superior performance of the fused Kolmogorov filter over existing screening methods by simulations and real data examples.