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Research PaperResearchia:202608.04079

Optimal Unambiguous DNFs and Alon-Saks-Seymour

Chirag Pabbaraju

Abstract

We construct unambiguous DNFs having width $O(n)$ but $0$-certificate complexity $Ω(n^2)$. By utilizing the special structure of these DNFs, we prove a lifting theorem with a constant-sized gadget that lifts the DNF to a communication problem, while losslessly translating the separation in certificate complexity to a separation in communication complexity. This leads to an optimal refutation of the Alon-Saks-Seymour conjecture, as well as an optimal communication lower bound for the Clique versu...

Submitted: August 4, 2026Subjects: Machine Learning; Data Science

Description / Details

We construct unambiguous DNFs having width O(n)O(n) but 00-certificate complexity Ω(n2)Ω(n^2). By utilizing the special structure of these DNFs, we prove a lifting theorem with a constant-sized gadget that lifts the DNF to a communication problem, while losslessly translating the separation in certificate complexity to a separation in communication complexity. This leads to an optimal refutation of the Alon-Saks-Seymour conjecture, as well as an optimal communication lower bound for the Clique versus Independent Set problem, improving the previous results of Balodis, Ben-David, Göös, Jain and Kothari (FOCS 2021, SICOMP 2023) by several doubly logarithmic factors. As further applications of our construction to query complexity and learning theory, we exhibit: (a) a family of Boolean functions that has an optimal quartic separation between certificate complexity and approximate degree, and (b) a sample compression lower bound of Ω(logc)Ω(\sqrt{\log c}) for multiclass concept classes over cc labels.


Source: arXiv:2608.02533v1 - http://arxiv.org/abs/2608.02533v1 PDF: https://arxiv.org/pdf/2608.02533v1 Original Link: http://arxiv.org/abs/2608.02533v1

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Date:
Aug 4, 2026
Topic:
Data Science
Area:
Machine Learning
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