arXiv subjects

Cameron Seth

Publications and source records attributed to Cameron Seth.

5 recordsLinked to original sources

arXiv2026

A quantitative container characterization of one-sided testability

We give a quantitative combinatorial characterization of size-oblivious one-sided testability in the dense graph model, resolving a question of Alon, Fischer, Newman, and Shapira. For hereditary graph properties, we prove that one-sided testability is quantitatively equivalent to the existence of suitable hypergraph containers, a central and widely used tool in modern combinatorics. Combining this equivalence with the Alon-Shapira notion of semi-hereditariness yields a quantitative characterization of arbitrary graph properties. The correspondence is effective in both directions and provides explicit translations between tester complexity and container parameters. Our proof is regularity-free and extends uniformly to every fixed finite relational signature of bounded arity, including digraphs, coloured graphs, and hypergraphs. As applications, we obtain quantitative closure results for partition properties and testers for properties defined by the existence of a linearly large induced substructure.

math.CO↗

arXiv2026

Testing the Independent Set Property in Hypergraphs

The optimal sample complexity of testing if an $n$-vertex graph has an independent set of size $\rho n$, or is $\varepsilon$-far from having an independent set of size $\rho n$, was established to be $\widetilde{O}(\rho^3/\varepsilon^2)$, in a notable result by Blais and Seth (SICOMP 2025). In contrast, for $q$-uniform hypergraphs, there is a significant gap between the best known upper and lower bounds, and there has been no progress on the problem for the last two decades. In this work, we prove a new upper bound of $\widetilde{O}\!\left(\frac{q\rho^{2q-3}}{\varepsilon^2 (q-2)!^2}\right)$ on the sample complexity of testing the $\rho$-independent set property. The previous best known upper bound was $\widetilde{O}\!\left(\frac{2^q q! \rho^{2q}}{\varepsilon^3}\right)$, due to Langberg (RANDOM 2004). This establishes the optimal dependence on $\varepsilon$ and gives an exponential improvement in the dependence on $q$. We prove our result via a new application of the hypergraph container method.

cs.DS↗

arXiv2025

A Tolerant Independent Set Tester

We give nearly optimal bounds on the sample complexity of $(\widetilde{\Omega}(\epsilon),\epsilon)$-tolerant testing the $\rho$-independent set property in the dense graph setting. In particular, we give an algorithm that inspects a random subgraph on $\widetilde{O}(\rho^3/\epsilon^2)$ vertices and, for some constant $c,$ distinguishes between graphs that have an induced subgraph of size $\rho n$ with fewer than $\frac{\epsilon}{c \log^4(1/\epsilon)} n^2$ edges from graphs for which every induced subgraph of size $\rho n$ has at least $\epsilon n^2$ edges. Our sample complexity bound matches, up to logarithmic factors, the recent upper bound by Blais and Seth (2023) for the non-tolerant testing problem, which is known to be optimal for the non-tolerant testing problem based on a lower bound by Feige, Langberg and Schechtman (2004). Our main technique is a new graph container lemma for sparse subgraphs instead of independent sets. We also show that our new lemma can be used to generalize one of the classic applications of the container method, that of counting independent sets in regular graphs, to counting sparse subgraphs in regular graphs.

cs.DS↗

arXiv2024

New Graph and Hypergraph Container Lemmas with Applications in Property Testing

The graph and hypergraph container methods are powerful tools with a wide range of applications across combinatorics. Recently, Blais and Seth (FOCS 2023) showed that the graph container method is particularly well-suited for the analysis of the natural canonical tester for two fundamental graph properties: having a large independent set and $k$-colorability. In this work, we show that the connection between the container method and property testing extends further along two different directions. First, we show that the container method can be used to analyze the canonical tester for many other properties of graphs and hypergraphs. We introduce a new hypergraph container lemma and use it to give an upper bound of $\widetilde{O}(kq^3/\epsilon)$ on the sample complexity of $\epsilon$-testing satisfiability, where $q$ is the number of variables per constraint and $k$ is the size of the alphabet. This is the first upper bound for the problem that is polynomial in all of $k$, $q$ and $1/\epsilon$. As a corollary, we get new upper bounds on the sample complexity of the canonical testers for hypergraph colorability and for every semi-homogeneous graph partition property. Second, we show that the container method can also be used to study the query complexity of (non-canonical) graph property testers. This result is obtained by introducing a new container lemma for the class of all independent set stars, a strict superset of the class of all independent sets. We use this container lemma to give a new upper bound of $\widetilde{O}(\rho^5/\epsilon^{7/2})$ on the query complexity of $\epsilon$-testing the $\rho$-independent set property. This establishes for the first time the non-optimality of the canonical tester for a non-homogeneous graph partition property.

cs.DS↗

arXiv2023

Testing Graph Properties with the Container Method

We establish nearly optimal sample complexity bounds for testing the $\rho$-clique property in the dense graph model. Specifically, we show that it is possible to distinguish graphs on $n$ vertices that have a $\rho n$-clique from graphs for which at least $\epsilon n^2$ edges must be added to form a $\rho n$-clique by sampling and inspecting a random subgraph on only $\tilde{O}(\rho^3/\epsilon^2)$ vertices. We also establish new sample complexity bounds for $\epsilon$-testing $k$-colorability. In this case, we show that a sampled subgraph on $\tilde{O}(k/\epsilon)$ vertices suffices to distinguish $k$-colorable graphs from those for which any $k$-coloring of the vertices causes at least $\epsilon n^2$ edges to be monochromatic. The new bounds for testing the $\rho$-clique and $k$-colorability properties are both obtained via new extensions of the graph container method. This method has been an effective tool for tackling various problems in graph theory and combinatorics. Our results demonstrate that it is also a powerful tool for the analysis of property testing algorithms.

cs.DS↗