On Sketching Quadratic Forms

Fuente: arXiv
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Main Authors: Andoni, Alexandr, Chen, Jiecao, Krauthgamer, Robert, Qin, Bo, Woodruff, David P., Zhang, Qin
Format: Preprint
Published: 2015
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author Andoni, Alexandr
Chen, Jiecao
Krauthgamer, Robert
Qin, Bo
Woodruff, David P.
Zhang, Qin
author_facet Andoni, Alexandr
Chen, Jiecao
Krauthgamer, Robert
Qin, Bo
Woodruff, David P.
Zhang, Qin
contents We undertake a systematic study of sketching a quadratic form: given an $n \times n$ matrix $A$, create a succinct sketch $\textbf{sk}(A)$ which can produce (without further access to $A$) a multiplicative $(1+ε)$-approximation to $x^T A x$ for any desired query $x \in \mathbb{R}^n$. While a general matrix does not admit non-trivial sketches, positive semi-definite (PSD) matrices admit sketches of size $Θ(ε^{-2} n)$, via the Johnson-Lindenstrauss lemma, achieving the "for each" guarantee, namely, for each query $x$, with a constant probability the sketch succeeds. (For the stronger "for all" guarantee, where the sketch succeeds for all $x$'s simultaneously, again there are no non-trivial sketches.) We design significantly better sketches for the important subclass of graph Laplacian matrices, which we also extend to symmetric diagonally dominant matrices. A sequence of work culminating in that of Batson, Spielman, and Srivastava (SIAM Review, 2014), shows that by choosing and reweighting $O(ε^{-2} n)$ edges in a graph, one achieves the "for all" guarantee. Our main results advance this front. $\bullet$ For the "for all" guarantee, we prove that Batson et al.'s bound is optimal even when we restrict to "cut queries" $x\in \{0,1\}^n$. In contrast, previous lower bounds showed the bound only for {\em spectral-sparsifiers}. $\bullet$ For the "for each" guarantee, we design a sketch of size $\tilde O(ε^{-1} n)$ bits for "cut queries" $x\in \{0,1\}^n$. We prove a nearly-matching lower bound of $Ω(ε^{-1} n)$ bits. For general queries $x \in \mathbb{R}^n$, we construct sketches of size $\tilde{O}(ε^{-1.6} n)$ bits.
format Preprint
id arxiv_https___arxiv_org_abs_1511_06099
institution arXiv
publishDate 2015
record_format arxiv
spellingShingle On Sketching Quadratic Forms
Andoni, Alexandr
Chen, Jiecao
Krauthgamer, Robert
Qin, Bo
Woodruff, David P.
Zhang, Qin
Data Structures and Algorithms
We undertake a systematic study of sketching a quadratic form: given an $n \times n$ matrix $A$, create a succinct sketch $\textbf{sk}(A)$ which can produce (without further access to $A$) a multiplicative $(1+ε)$-approximation to $x^T A x$ for any desired query $x \in \mathbb{R}^n$. While a general matrix does not admit non-trivial sketches, positive semi-definite (PSD) matrices admit sketches of size $Θ(ε^{-2} n)$, via the Johnson-Lindenstrauss lemma, achieving the "for each" guarantee, namely, for each query $x$, with a constant probability the sketch succeeds. (For the stronger "for all" guarantee, where the sketch succeeds for all $x$'s simultaneously, again there are no non-trivial sketches.) We design significantly better sketches for the important subclass of graph Laplacian matrices, which we also extend to symmetric diagonally dominant matrices. A sequence of work culminating in that of Batson, Spielman, and Srivastava (SIAM Review, 2014), shows that by choosing and reweighting $O(ε^{-2} n)$ edges in a graph, one achieves the "for all" guarantee. Our main results advance this front. $\bullet$ For the "for all" guarantee, we prove that Batson et al.'s bound is optimal even when we restrict to "cut queries" $x\in \{0,1\}^n$. In contrast, previous lower bounds showed the bound only for {\em spectral-sparsifiers}. $\bullet$ For the "for each" guarantee, we design a sketch of size $\tilde O(ε^{-1} n)$ bits for "cut queries" $x\in \{0,1\}^n$. We prove a nearly-matching lower bound of $Ω(ε^{-1} n)$ bits. For general queries $x \in \mathbb{R}^n$, we construct sketches of size $\tilde{O}(ε^{-1.6} n)$ bits.
title On Sketching Quadratic Forms
topic Data Structures and Algorithms
url https://arxiv.org/abs/1511.06099