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arXiv · 2205.01023

A Unified Approach to Discrepancy Minimization

Nikhil Bansal·Aditi Laddha·Santosh S. Vempala
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Abstract

We study a unified approach and algorithm for constructive discrepancy minimization based on a stochastic process. By varying the parameters of the process, one can recover various state-of-the-art results. We demonstrate the flexibility of the method by deriving a discrepancy bound for smoothed instances, which interpolates between known bounds for worst-case and random instances.

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Nikhil Bansal, Aditi Laddha, Santosh S. Vempala. 2022-05-02. A Unified Approach to Discrepancy Minimization. https://arxiv.org/abs/2205.01023

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