Counting Small Induced Subgraphs: Hardness via Fourier Analysis
Radu Curticapean, Daniel Neuen

TL;DR
This paper establishes tight ETH-based lower bounds for counting small induced subgraphs with specific properties, using Fourier analysis and algebraic techniques, advancing understanding of computational hardness in graph problems.
Contribution
It introduces new ETH-based lower bounds for counting induced subgraphs with properties like edge-monotonicity, using Fourier analysis and algebraic methods, extending previous results.
Findings
ETH rules out $n^{o(k)}$ algorithms for edge-monotone properties
Lower bounds hold for counting modulo fixed primes
Results generalize to weighted graphs and density exclusions
Abstract
For a fixed graph property and integer , consider the problem of counting the induced -vertex subgraphs satisfying in an input graph . This problem can be solved by brute-force in time . Under ETH, we prove several lower bounds on the optimal exponent in this running time: If is edge-monotone (i.e., closed under deleting edges), then ETH rules out time algorithms for this problem. This strengthens a recent lower bound by D\"{o}ring, Marx and Wellnitz [STOC 2024]. Our result also holds for counting modulo fixed primes. If at most graphs on vertices satisfy , for some , then ETH also rules out an exponent of . This holds even when the graphs in have arbitrary individual weights, generalizing previous results for hereditary properties by Focke and Roth…
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Taxonomy
TopicsMachine Learning and Algorithms · Machine Learning and Data Classification
