Hardness of Bichromatic Closest Pair with Jaccard Similarity

Consider collections $\mathcal{A}$ and $\mathcal{B}$ of red and blue sets, respectively. Bichromatic Closest Pair is the problem of finding a pair from $\mathcal{A}\times \mathcal{B}$ that has similarity higher than a given threshold according to some similarity measure. Our focus here is the classic Jaccard similarity $|\textbf{a}\cap \textbf{b}|/|\textbf{a}\cup \textbf{b}|$ for $(\textbf{a},\textbf{b})\in \mathcal{A}\times \mathcal{B}$. We consider the approximate version of the problem where we are given thresholds $j_1>j_2$ and wish to return a pair from $\mathcal{A}\times \mathcal{B}$ that has Jaccard similarity higher than $j_2$ if there exists a pair in $\mathcal{A}\times \mathcal{B}$ with Jaccard similarity at least $j_1$. The classic locality sensitive hashing (LSH) algorithm of Indyk and Motwani (STOC '98), instantiated with the MinHash LSH function of Broder et al., solves this problem in $\tilde O(n^{2-\delta})$ time if $j_1\ge j_2^{1-\delta}$. In particular, for $\delta=\Omega(1)$, the approximation ratio $j_1/j_2=1/j_2^{\delta}$ increases polynomially in $1/j_2$. In this paper we give a corresponding hardness result. Assuming the Orthogonal Vectors Conjecture (OVC), we show that there cannot be a general solution that solves the Bichromatic Closest Pair problem in $O(n^{2-\Omega(1)})$ time for $j_1/j_2=1/j_2^{o(1)}$. Specifically, assuming OVC, we prove that for any $\delta>0$ there exists an $\varepsilon>0$ such that Bichromatic Closest Pair with Jaccard similarity requires time $\Omega(n^{2-\delta})$ for any choice of thresholds $j_2<j_1<1-\delta$, that satisfy $j_1\le j_2^{1-\varepsilon}$

Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming

We revisit Nisan's classical pseudorandom generator (PRG) for space-bounded computation (STOC 1990) and its applications in streaming algorithms. We describe a new generator, HashPRG, that can be thought of as a symmetric version of Nisan's generator over larger alphabets. Our generator allows a trade-off between seed length and the time needed to compute a given block of the generator's output. HashPRG can be used to obtain derandomizations with much better update time and \emph{without sacrificing space} for a large number of data stream algorithms, such as $F_p$ estimation in the parameter regimes $p > 2$ and $0 < p < 2$ and CountSketch with tight estimation guarantees as analyzed by Minton and Price (SODA 2014) which assumed access to a random oracle. We also show a recent analysis of Private CountSketch can be derandomized using our techniques. For a $d$-dimensional vector $x$ being updated in a turnstile stream, we show that $\|x\|_{\infty}$ can be estimated up to an additive error of $\varepsilon\|x\|_{2}$ using $O(\varepsilon^{-2}\log(1/\varepsilon)\log d)$ bits of space. Additionally, the update time of this algorithm is $O(\log 1/\varepsilon)$ in the Word RAM model. We show that the space complexity of this algorithm is optimal up to constant factors. However, for vectors $x$ with $\|x\|_{\infty} = \Theta(\|x\|_{2})$, we show that the lower bound can be broken by giving an algorithm that uses $O(\varepsilon^{-2}\log d)$ bits of space which approximates $\|x\|_{\infty}$ up to an additive error of $\varepsilon\|x\|_{2}$. We use our aforementioned derandomization of the CountSketch data structure to obtain this algorithm, and using the time-space trade off of HashPRG, we show that the update time of this algorithm is also $O(\log 1/\varepsilon)$ in the Word RAM model.Comment: Minor writing improvement

Udenfor museet - indenfor murene

Artiklen fremstiller et aktionsforskningsinspireret formidlingsprojekt (Rødder) i Storstrøm statsfængsle, der gennem en serie prøvehandlinger eksperimenterer med kulturhistoriske formidling til fængslets indsatte. På baggrund af 5 kvalitative interview med indsatte diskuteres museets rolle som dannelsesaktør og hvordan viden om fortiden kan blive et fælles tredje i unge voksnes samtaler om identitet og tilknytning

Udenfor museet - indenfor murene

Artiklen fremstiller et aktionsforskningsinspireret formidlingsprojekt (Rødder) i Storstrøm statsfængsle, der gennem en serie prøvehandlinger eksperimenterer med kulturhistoriske formidling til fængslets indsatte. På baggrund af 5 kvalitative interview med indsatte diskuteres museets rolle som dannelsesaktør og hvordan viden om fortiden kan blive et fælles tredje i unge voksnes samtaler om identitet og tilknytning

Triangle Counting in Dynamic Graph Streams

Estimating the number of triangles in graph streams using a limited amount of memory has become a popular topic in the last decade. Different variations of the problem have been studied, depending on whether the graph edges are provided in an arbitrary order or as incidence lists. However, with a few exceptions, the algorithms have considered {\em insert-only} streams. We present a new algorithm estimating the number of triangles in {\em dynamic} graph streams where edges can be both inserted and deleted. We show that our algorithm achieves better time and space complexity than previous solutions for various graph classes, for example sparse graphs with a relatively small number of triangles. Also, for graphs with constant transitivity coefficient, a common situation in real graphs, this is the first algorithm achieving constant processing time per edge. The result is achieved by a novel approach combining sampling of vertex triples and sparsification of the input graph. In the course of the analysis of the algorithm we present a lower bound on the number of pairwise independent 2-paths in general graphs which might be of independent interest. At the end of the paper we discuss lower bounds on the space complexity of triangle counting algorithms that make no assumptions on the structure of the graph.Comment: New version of a SWAT 2014 paper with improved result