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Hamed Hatami

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8 papers
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8

FOCS Conference 2024 Conference Paper

Sparse Graph Counting and Kelley-Meka Bounds for Binary Systems

  • Yuval Filmus
  • Hamed Hatami
  • Kaave Hosseini
  • Esty Kelman

In a recent breakthrough, Kelley and Meka (FOCS 2023) obtained a strong upper bound on the density of sets of integers without non-trivial three-term arithmetic progressions. In this work, we extend their result, establishing similar bounds for all linear patterns defined by binary systems of linear forms, where “binary” indicates that every linear form depends on exactly two variables. Prior to our work, no strong bounds were known for such systems even in the finite field model setting. A key ingredient in our proof is a graph counting lemma. The classical graph counting lemma, developed by Thomason (Random Graphs 1985) and Chung, Graham, and Wilson (Combinatorica 1989), is a fundamental tool in combinatorics. For a fixed graph $H$, it states that the number of copies of $H$ in a pseudorandom graph $G$ is similar to the number of copies of $H$ in a purely random graph with the same edge density as $G$. However, this lemma is only non-trivial when $G$ is a dense graph. In this work, we prove a graph counting lemma that is also effective when $G$ is sparse. Moreover, our lemma is well-suited for density increment arguments in additive number theory. As an immediate application, we obtain a strong bound for the Turán problem in abelian Cayley sum graphs: let $\Gamma$ be a finite abelian group with odd order. If a Cayley sum graph on $\Gamma$ does not contain any r-elique as a sub graph, it must have at most $2^{-\Omega_r\left(\log ^{1 / 16}\vert \Gamma\vert \right)} \cdot\vert \Gamma\vert ^2$ edges. These results hinge on the technology developed by Kelley and Meka and the follow-up work by Kelley, Lovett, and Meka (STOC 2024).

STOC Conference 2023 Conference Paper

A Borsuk-Ulam Lower Bound for Sign-Rank and Its Applications

  • Hamed Hatami
  • Kaave Hosseini
  • Xiang Meng

We introduce a new topological argument based on the Borsuk-Ulam theorem to prove a lower bound on sign-rank. This result implies the strongest possible separation between randomized and unbounded-error communication complexity. More precisely, we show that for a particular range of parameters, the randomized communication complexity of the Gap Hamming Distance problem is O (1) while its unbounded-error communication complexity is Ω(log( n )). Previously, it was unknown whether the unbounded-error communication complexity could be asymptotically larger than the randomized communication In connection to learning theory, we prove that, despite its learnability properties, the class of large margin half-spaces in ℝ d is genuinely high-dimensional, i.e., it cannot be embedded in d −1 . This result is closely related to a recent conjecture of Alon, Hanneke, Holzman, and Moran (FOCS 2021) about the VC dimension of this class. Our final application is to the theory of dimension reductions. The Johnson-Lindenstrauss theorem implies that any set of N unit vectors is embeddable in dimension O (γ −2 log N ) without altering the signs of those pairwise inner products that have absolute values at least γ>0. Our result establishes the tightness of this bound, which answers a question of Linial, Mendelson, Schechtman, and Shraibman (Combinatorica, 27(2007)) in the case of partial functions.

FOCS Conference 2022 Conference Paper

The Implicit Graph Conjecture is False

  • Hamed Hatami
  • Pooya Hatami

An efficient implicit representation of an n-vertex graph G in a family $\mathcal{F}$ of graphs assigns to each vertex of G a binary code of length O(log n) so that the adjacency between every pair of vertices can be determined only as a function of their codes. This function can depend on the family but not on the individual graph. Every family of graphs admitting such a representation contains at most $2^{O(n\log(n))}$ graphs on n vertices, and thus has at most factorial speed of growth. The Implicit Graph Conjecture states that, conversely, every hereditary graph family with at most factorial speed of growth admits an efficient implicit representation. We refute this conjecture by establishing the existence of hereditary graph families with factorial speed of growth that require codes of length $n^{\Omega(1)}$.

FOCS Conference 2016 Conference Paper

Structure of Protocols for XOR Functions

  • Hamed Hatami
  • Kaave Hosseini
  • Shachar Lovett

Let f be a boolean function on n variables. Its associated XOR function is the two-party function F(x, y) = f(x xor y). We show that, up to polynomial factors, the deterministic communication complexity of F is equal to the parity decision tree complexity of f. This relies on a novel technique of entropy reduction for protocols, combined with existing techniques in Fourier analysis and additive combinatorics.

FOCS Conference 2013 Conference Paper

Estimating the Distance from Testable Affine-Invariant Properties

  • Hamed Hatami
  • Shachar Lovett

Let P be an affine invariant property of multivariate functions over a constant size finite field. We show that if P is locally testable with a constant number of queries, then one can estimate the distance of a function f from P with a constant number of queries. This was previously unknown even for simple properties such as cubic polynomials over the binary field. Our test is simple: take a restriction of f to a constant dimensional affine subspace, and measure its distance from P. We show that by choosing the dimension large enough, this approximates with high probability the global distance of f from P. The analysis combines the approach of Fischer and Newman [SIAM J. Comp 2007] who established a similar result for graph properties, with recently developed tools in higher order Fourier analysis, in particular those developed in Bhattacharyya et al. [STOC 2013].

STOC Conference 2011 Conference Paper

Correlation testing for affine invariant properties on F p n in the high error regime

  • Hamed Hatami
  • Shachar Lovett

Recently there has been much interest in Gowers uniformity norms from the perspective of theoretical computer science. This is mainly due to the fact that these norms provide a method for testing whether the maximum correlation of a function f:F p n -> F p with polynomials of degree at most d ≤ p is non-negligible, while making only a constant number of queries to the function. This is an instance of correlation testing . In this framework, a fixed test is applied to a function, and the acceptance probability of the test is dependent on the correlation of the function from the property. This is an analog of proximity oblivious testing , a notion coined by Goldreich and Ron, in the high error regime. We study in this work general properties which are affine invariant and which are correlation testable using a constant number of queries. We show that any such property (as long as the field size is not too small) can in fact be tested by the Gowers uniformity test, and hence having correlation with the property is equivalent to having correlation with degree d polynomials for some fixed d. We stress that our result holds also for non-linear properties which are affine invariant. This completely classifies affine invariant properties which are correlation testable. The proof is based on higher-order Fourier analysis, where we establish a new approximate orthogonality for structures defined by linear forms. In particular, this resolves an open problem posed by Gowers and Wolf. Another ingredient is a nontrivial extension of a graph theoretical theorem of Erdos, Lovasz and Spencer to the context of additive number theory.

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