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Related papers: Almost Euclidean subspaces of \ell_1^N via expande…

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It is well known that R^N has subspaces of dimension proportional to N on which the \ell_1 norm is equivalent to the \ell_2 norm; however, no explicit constructions are known. Extending earlier work by Artstein--Avidan and Milman, we prove…

Functional Analysis · Mathematics 2009-04-12 Shachar Lovett , Sasha Sodin

It has been known since 1970's that the N-dimensional $\ell_1$-space contains nearly Euclidean subspaces whose dimension is $\Omega(N)$. However, proofs of existence of such subspaces were probabilistic, hence non-constructive, which made…

Metric Geometry · Mathematics 2010-09-14 Piotr Indyk , Stanislaw Szarek

The subspace design property for additive codes is a higher-dimensional generalization of the minimum distance property. As shown recently by Brakensiek, Chen, Dhar and Zhang, it implies that the code has similar performance as random…

Information Theory · Computer Science 2026-04-17 Rohan Goyal , Venkatesan Guruswami , Jun-Ting Hsieh

We prove that every $n$-point metric space of negative type (and, in particular, every $n$-point subset of $L_1$) embeds into a Euclidean space with distortion $O(\sqrt{\log n} \cdot\log \log n)$, a result which is tight up to the iterated…

Metric Geometry · Mathematics 2007-05-23 Sanjeev Arora , James R. Lee , Assaf Naor

We show how to compute the edit distance between two strings of length n up to a factor of 2^{\~O(sqrt(log n))} in n^(1+o(1)) time. This is the first sub-polynomial approximation algorithm for this problem that runs in near-linear time,…

Data Structures and Algorithms · Computer Science 2011-09-27 Alexandr Andoni , Krzysztof Onak

We present the first polynomial-time algorithm for computing a near-optimal \emph{flow}-expander decomposition. Given a graph $G$ and a parameter $\phi$, our algorithm removes at most a $\phi\log^{1+o(1)}n$ fraction of edges so that every…

Data Structures and Algorithms · Computer Science 2026-04-29 Nikhil Bansal , Arun Jambulapati , Thatchaphol Saranurak

We study uniquely decodable codes and list decodable codes in the high-noise regime, specifically codes that are uniquely decodable from $\frac{1-\varepsilon}{2}$ fraction of errors and list decodable from $1-\varepsilon$ fraction of…

Information Theory · Computer Science 2024-11-06 Xin Li , Songtao Mao

Let $G =<S>$ be a solvable permutation group of the symmetric group $S_n$ given as input by the generating set $S$. We give a deterministic polynomial-time algorithm that computes an \emph{expanding generating set} of size $\tilde{O}(n^2)$…

Computational Complexity · Computer Science 2012-01-17 V. Arvind , Partha Mukhopadhyay , Prajakta Nimbhorkar , Yadu Vasudev

We give the first O(m polylog(n)) time algorithms for approximating maximum flows in undirected graphs and constructing polylog(n) -quality cut-approximating hierarchical tree decompositions. Our algorithm invokes existing algorithms for…

Data Structures and Algorithms · Computer Science 2015-11-18 Richard Peng

We show that a subspace of of $\ell_\infty^N$ of dimension $n>(\log N\log \log N)^2$ contains $2$-isomorphic copies of $\ell_\infty^k$ where $k$ tends to infinity with $n/(\log N\log \log N)^2$. More precisely, for every $\eta>0$, we show…

Functional Analysis · Mathematics 2018-12-11 Gideon Schechtman , Nicole Tomczak--Jaegermann

We give an embedding of the Poincar\'e halfspace $H^D$ into a discrete metric space based on a binary tiling of $H^D$, with additive distortion $O(\log D)$. It yields the following results. We show that any subset $P$ of $n$ points in $H^D$…

Computational Geometry · Computer Science 2024-04-02 Eunku Park , Antoine Vigneron

The construction of $r$-nets offers a powerful tool in computational and metric geometry. We focus on high-dimensional spaces and present a new randomized algorithm which efficiently computes approximate $r$-nets with respect to Euclidean…

Computational Geometry · Computer Science 2017-05-09 Georgia Avarikioti , Ioannis Z. Emiris , Loukas Kavouras , Ioannis Psarros

We present an explicit and efficient algebraic construction of capacity-achieving list decodable codes with both constant alphabet and constant list sizes. More specifically, for any $R \in (0,1)$ and $\epsilon>0$, we give an algebraic…

Computational Complexity · Computer Science 2021-06-11 Zeyu Guo , Noga Ron-Zewi

We develop new approximation algorithms for classical graph and set problems in the RAM model under space constraints. As one of our main results, we devise an algorithm for d-Hitting Set that runs in time n^{O(d^2 + d/\epsilon})}, uses…

Data Structures and Algorithms · Computer Science 2021-02-23 Arindam Biswas , Venkatesh Raman , Saket Saurabh

We present a near-linear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed epsilon>0, it can compute a (log n)^O(1/epsilon)…

Data Structures and Algorithms · Computer Science 2010-05-24 Alexandr Andoni , Robert Krauthgamer , Krzysztof Onak

Thorup [FOCS'01, JACM'04] and Klein [SODA'01] independently showed that there exists a $(1+\epsilon)$-approximate distance oracle for planar graphs with $O(n (\log n)\epsilon^{-1})$ space and $O(\epsilon^{-1})$ query time. While the…

Data Structures and Algorithms · Computer Science 2022-07-13 Hung Le

In this paper, we present a linear-time approximation scheme for $k$-means clustering of \emph{incomplete} data points in $d$-dimensional Euclidean space. An \emph{incomplete} data point with $\Delta>0$ unspecified entries is represented as…

Computational Geometry · Computer Science 2021-06-29 Kyungjin Cho , Eunjin Oh

We give a deterministic polynomial space construction for nearly optimal eps-nets with respect to any input n-dimensional convex body K and norm |.|. More precisely, our algorithm can build and iterate over an eps-net of K with respect to…

Computational Complexity · Computer Science 2013-12-04 Daniel Dadush

We study the almost periods of the eigenmodes of flat planar manifolds in the high energy limit. We prove in particular that the Gaussian Arithmetic Random Waves replicate almost identically at a scale at most ${\ell}$n := n -- 1 2 exp…

Probability · Mathematics 2023-03-20 Loïc Thomassey , Raphaël Lachièze-Rey

The Johnson-Lindenstrauss lemma is a fundamental result in probability with several applications in the design and analysis of algorithms in high dimensional geometry. Most known constructions of linear embeddings that satisfy the…

Data Structures and Algorithms · Computer Science 2015-03-17 Raghu Meka
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