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We show that a constant factor approximation of the shortest and closest lattice vector problem in any norm can be computed in time $2^{0.802\, n}$. This contrasts the corresponding $2^n$ time, (gap)-SETH based lower bounds for these…

Data Structures and Algorithms · Computer Science 2021-10-07 Thomas Rothvoss , Moritz Venzin

$ \newcommand{\eps}{\varepsilon} \newcommand{\problem}[1]{\ensuremath{\mathrm{#1}} } \newcommand{\CVP}{\problem{CVP}} \newcommand{\SVP}{\problem{SVP}} \newcommand{\CVPP}{\problem{CVPP}} \newcommand{\ensuremath}[1]{#1} $For odd integers $p…

Computational Complexity · Computer Science 2019-01-28 Huck Bennett , Alexander Golovnev , Noah Stephens-Davidowitz

The Closest Vector Problem (CVP) is a computational problem in lattices that is central to modern cryptography. The study of its fine-grained complexity has gained momentum in the last few years, partly due to the upcoming deployment of…

Data Structures and Algorithms · Computer Science 2025-01-08 Amir Abboud , Rajendra Kumar

We show that, assuming NP $\not\subseteq$ $\cap_{\delta > 0}$DTIME$\left(\exp{n^\delta}\right)$, the shortest vector problem for lattices of rank $n$ in any finite $\ell_p$ norm is hard to approximate within a factor of $2^{(\log n)^{1 -…

Computational Complexity · Computer Science 2026-04-07 Isaac M Hair , Amit Sahai

We show a number of fine-grained hardness results for the Closest Vector Problem in the $\ell_p$ norm ($\mathrm{CVP}_p$), and its approximate and non-uniform variants. First, we show that $\mathrm{CVP}_p$ cannot be solved in…

Computational Complexity · Computer Science 2021-08-10 Divesh Aggarwal , Huck Bennett , Alexander Golovnev , Noah Stephens-Davidowitz

In this work, we give provable sieving algorithms for the Shortest Vector Problem (SVP) and the Closest Vector Problem (CVP) on lattices in $\ell_p$ norm ($1\leq p\leq\infty$). The running time we obtain is better than existing provable…

Data Structures and Algorithms · Computer Science 2021-12-21 Priyanka Mukhopadhyay

In this work, we exhibit a hierarchy of polynomial time algorithms solving approximate variants of the Closest Vector Problem (CVP). Our first contribution is a heuristic algorithm achieving the same distance tradeoff as HSVP algorithms,…

Data Structures and Algorithms · Computer Science 2020-06-12 Thomas Espitau , Paul Kirchner

We present a substantially more efficient variant, both in terms of running time and size of preprocessing advice, of the algorithm by Liu, Lyubashevsky, and Micciancio for solving CVPP (the preprocessing version of the Closest Vector…

Data Structures and Algorithms · Computer Science 2019-01-28 Daniel Dadush , Oded Regev , Noah Stephens-Davidowitz

The $\ell_p$ linear regression problem is to minimize $f(x)=||Ax-b||_p$ over $x\in\mathbb{R}^d$, where $A\in\mathbb{R}^{n\times d}$, $b\in \mathbb{R}^n$, and $p>0$. To avoid overfitting and bound $||x||_2$, the constrained $\ell_p$…

Machine Learning · Computer Science 2019-02-28 Ibrahim Jubran , David Cohn , Dan Feldman

We give a deterministic algorithm for solving the (1+eps)-approximate Closest Vector Problem (CVP) on any n dimensional lattice and any norm in 2^{O(n)}(1+1/eps)^n time and 2^n poly(n) space. Our algorithm builds on the lattice point…

Data Structures and Algorithms · Computer Science 2013-01-01 Daniel Dadush , Gabor Kun

$ \newcommand{\SVP}{\textsf{SVP}} \newcommand{\CVP}{\textsf{CVP}} \newcommand{\eps}{\varepsilon} $We show a number of reductions between the Shortest Vector Problem and the Closest Vector Problem over lattices in different $\ell_p$ norms…

Data Structures and Algorithms · Computer Science 2021-04-15 Divesh Aggarwal , Yanlin Chen , Rajendra Kumar , Zeyong Li , Noah Stephens-Davidowitz

We establish deterministic hardness of approximation results for the Shortest Vector Problem in $\ell_p$ norm ($\mathsf{SVP}_p$) and for Unique-SVP ($\mathsf{uSVP}_p$) for all $p > 2$. Previously, no deterministic hardness results were…

Computational Complexity · Computer Science 2025-10-21 Yahli Hecht , Muli Safra

Bl\"omer and Seifert showed that $\mathsf{SIVP}_2$ is NP-hard to approximate by giving a reduction from $\mathsf{CVP}_2$ to $\mathsf{SIVP}_2$ for constant approximation factors as long as the $\mathsf{CVP}$ instance has a certain property.…

Computational Complexity · Computer Science 2020-11-03 Divesh Aggarwal , Eldon Chung

$ \newcommand{\problem}[1]{\ensuremath{\mathrm{#1}} } \newcommand{\SVP}{\problem{SVP}} \newcommand{\ensuremath}[1]{#1} $We prove the following quantitative hardness results for the Shortest Vector Problem in the $\ell_p$ norm ($\SVP_p$),…

Computational Complexity · Computer Science 2019-01-23 Divesh Aggarwal , Noah Stephens-Davidowitz

Recent work [BGS17,ABGS19] has shown SETH hardness of CVP in the $\ell_p$ norm for any $p$ that is not an even integer. This result was shown by giving a Karp reduction from $k$-SAT on $n$ variables to CVP on a lattice of rank $n$. In this…

Computational Complexity · Computer Science 2023-11-28 Divesh Aggarwal , Rajendra Kumar

We present algorithms for the $(1+\epsilon)$-approximate version of the closest vector problem for certain norms. The currently fastest algorithm (Dadush and Kun 2016) for general norms has running time of $2^{O(n)} (1/\epsilon)^n$. We…

Data Structures and Algorithms · Computer Science 2021-11-03 Márton Naszódi , Moritz Venzin

We obtain hardness of approximation results for the $\ell_p$-Shortest Path problem, a variant of the classic Shortest Path problem with vector costs. For every integer $p \in [2,\infty)$, we show a hardness of $\Omega(p(\log n / \log^2\log…

Data Structures and Algorithms · Computer Science 2025-10-27 Charlie Carlson , Yury Makarychev , Ron Mosenzon

A particular instance of the Shortest Vector Problem (SVP) appears in the context of Compute-and-Forward. Despite the NP-hardness of the SVP, we will show that this certain instance can be solved in complexity order $O(n\psi\log(n\psi))$…

Information Theory · Computer Science 2017-11-28 Saeid Sahraei , Michael Gastpar

Lattice-based cryptography has recently emerged as a prime candidate for efficient and secure post-quantum cryptography. The two main hard problems underlying its security are the shortest vector problem (SVP) and the closest vector problem…

Cryptography and Security · Computer Science 2019-10-04 Thijs Laarhoven

Blomer and Naewe[BN09] modified the randomized sieving algorithm of Ajtai, Kumar and Sivakumar[AKS01] to solve the shortest vector problem (SVP). The algorithm starts with $N = 2^{O(n)}$ randomly chosen vectors in the lattice and employs a…

Data Structures and Algorithms · Computer Science 2018-05-16 Divesh Aggarwal , Priyanka Mukhopadhyay
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