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In this paper, we consider the fault-tolerant $k$-median problem and give the \emph{first} constant factor approximation algorithm for it. In the fault-tolerant generalization of classical $k$-median problem, each client $j$ needs to be…

Data Structures and Algorithms · Computer Science 2014-01-27 Mohammadtaghi Hajiaghayi , Wei Hu , Jian Li , Shi Li , Barna Saha

We consider the problem of testing graph cluster structure: given access to a graph $G=(V, E)$, can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph?…

Data Structures and Algorithms · Computer Science 2018-09-19 Ashish Chiplunkar , Michael Kapralov , Sanjeev Khanna , Aida Mousavifar , Yuval Peres

We design a nonadaptive algorithm that, given oracle access to a function $f: \{0,1\}^n \to \{0,1\}$ which is $\alpha$-far from monotone, makes poly$(n, 1/\alpha)$ queries and returns an estimate that, with high probability, is an…

Data Structures and Algorithms · Computer Science 2021-02-26 Ramesh Krishnan S. Pallavoor , Sofya Raskhodnikova , Erik Waingarten

We consider the problem of testing whether a Boolean function has Fourier degree $\leq k$ or it is $\epsilon$-far from any Boolean function with Fourier degree $\leq k$. We improve the known lower bound of $\Omega(k)$ \cite{BBM11,CGM10}, to…

Computational Complexity · Computer Science 2013-08-27 Pooya Hatami

In discrete k-center and k-median clustering, we are given a set of points P in a metric space M, and the task is to output a set C \subseteq ? P, |C| = k, such that the cost of clustering P using C is as small as possible. For k-center,…

Data Structures and Algorithms · Computer Science 2013-07-10 Nirman Kumar , Benjamin Raichel

This paper introduces the correlation-of-divergency coefficient, c-delta, a custom statistical measure designed to quantify the similarity of internal divergence patterns between two groups of values. Unlike conventional correlation…

Methodology · Statistics 2026-03-10 Johan F. Hoorn

Equivalence testing, a fundamental problem in the field of distribution testing, seeks to infer if two unknown distributions on $[n]$ are the same or far apart in the total variation distance. Conditional sampling has emerged as a powerful…

Data Structures and Algorithms · Computer Science 2024-03-08 Diptarka Chakraborty , Sourav Chakraborty , Gunjan Kumar , Kuldeep S. Meel

Spatial interaction between two or more classes or species has important implications in various fields and causes multivariate patterns such as segregation or association. Segregation occurs when members of a class or species are more…

Methodology · Statistics 2009-02-09 Elvan Ceyhan

We consider the problem of approximating and learning disjunctions (or equivalently, conjunctions) on symmetric distributions over $\{0,1\}^n$. Symmetric distributions are distributions whose PDF is invariant under any permutation of the…

Machine Learning · Computer Science 2015-05-27 Vitaly Feldman , Pravesh Kothari

We prove a lower bound of $\Omega(n^{1/2 - c})$, for all $c>0$, on the query complexity of (two-sided error) non-adaptive algorithms for testing whether an $n$-variable Boolean function is monotone versus constant-far from monotone. This…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Anindya De , Rocco A. Servedio , Li-Yang Tan

Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation,…

Statistics Theory · Mathematics 2008-12-18 Gábor J. Székely , Maria L. Rizzo , Nail K. Bakirov

An $m \times n$ matrix $\mathsf{A}$ with column supports $\{S_i\}$ is $k$-separable if the disjunctions $\bigcup_{i \in \mathcal{K}} S_i$ are all distinct over all sets $\mathcal{K}$ of cardinality $k$. While a simple counting bound shows…

Combinatorics · Mathematics 2017-11-27 Matthew Aldridge , Leonardo Baldassini , Karen Gunderson

In this tutorial, we will survey known results on the complexity of conjunctive query evaluation in different settings, ranging from Boolean queries over counting to more complex models like enumeration and direct access. A particular focus…

Databases · Computer Science 2025-06-24 Stefan Mengel

This paper considers the problem of approximating a Boolean function $f$ using another Boolean function from a specified class. Two classes of approximating functions are considered: $k$-juntas, and linear Boolean functions. The $n$ input…

Information Theory · Computer Science 2019-07-09 Mohsen Heidari , S. Sandeep Pradhan , Ramji Venkataramanan

Quantum Mechanics (QM) predicts the correlation between measurements performed in remote regions of a spatially spread entangled state to be higher than allowed by the intuitive concepts of Locality and Realism (LR). This high correlation…

Quantum Physics · Physics 2019-04-17 Alejandro Hnilo , Mónica Agüero

The cardinal direction calculus (CDC) proposed by Goyal and Egenhofer is a very expressive qualitative calculus for directional information of extended objects. Early work has shown that consistency checking of complete networks of basic…

Artificial Intelligence · Computer Science 2010-11-05 Weiming Liu , Sanjiang Li

This paper studies the problem of testing if an input (Gamma,*), where Gamma is a finite set of unknown size and * is a binary operation over Gamma given as an oracle, is close to a specified class of groups. Friedl et al. [Efficient…

Data Structures and Algorithms · Computer Science 2021-10-05 Francois Le Gall , Yuichi Yoshida

A q-query locally testable code (LTC) is an error correcting code that can be tested by a randomized algorithm that reads at most q symbols from the given word. An important question is whether there exist LTCs that have the ccc-property:…

Computational Complexity · Computer Science 2010-12-14 Irit Dinur , Tali Kaufman

A pair of probability distributions over $\{0,1\}^n$ is said to be $(k,\delta)$-wise indistinguishable if all of the size $k$ marginals are within statistical distance at most $\delta$. Previous works introduced this concept and study when…

Computational Complexity · Computer Science 2026-05-14 Christopher Williamson

We consider the problem of determining which classes of functions can be tested more efficiently than they can be learned, in the distribution-free sample-based model that corresponds to the standard PAC learning setting. Our main result…

Machine Learning · Computer Science 2020-12-08 Eric Blais , Renato Ferreira Pinto , Nathaniel Harms
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