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We introduce kernel thinning, a new procedure for compressing a distribution $\mathbb{P}$ more effectively than i.i.d. sampling or standard thinning. Given a suitable reproducing kernel $\mathbf{k}_{\star}$ and $O(n^2)$ time, kernel…

Machine Learning · Statistics 2024-05-14 Raaz Dwivedi , Lester Mackey

Phase retrieval in real or complex Hilbert spaces is the task of recovering a vector, up to an overall unimodular multiplicative constant, from magnitudes of linear measurements. In this paper, we assume that the vector is normalized, but…

Probability · Mathematics 2019-11-19 Dylan Domel-White , Bernhard G. Bodmann

Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

The previously fastest algorithm for deciding the existence of an independent cut had a runtime of $\mathcal{O}^*(1.4423^n)$, where $n$ is the order of the input graph. We improve this to $\mathcal{O}^*(1.4143^n)$. In fact, we prove a…

Data Structures and Algorithms · Computer Science 2025-05-22 Vsevolod Chernyshev , Johannes Rauch , Dieter Rautenbach , Liliia Redina

An approximate sparse recovery system consists of parameters $k,N$, an $m$-by-$N$ measurement matrix, $\Phi$, and a decoding algorithm, $\mathcal{D}$. Given a vector, $x$, the system approximates $x$ by $\widehat x =\mathcal{D}(\Phi x)$,…

Data Structures and Algorithms · Computer Science 2014-02-10 Anna C. Gilbert , Yi Li , Ely Porat , Martin J. Strauss

One of the most important processing steps in any analysis pipeline is handling missing data. Traditional approaches simply delete any sample or feature with missing elements. Recent imputation methods replace missing data based on assumed…

Databases · Computer Science 2024-05-03 Kenneth Smith , Sharlee Climer

We study the problem of edge partitioning, where the goal is to partition the edge set of a graph into several parts. The replication factor of a vertex $v$ is the number of parts that contain edges incident to $v$. The goal is to minimize…

Discrete Mathematics · Computer Science 2026-05-08 Alexander Yakunin , Andrey Kupavskii , Alexander Sushin , Stanislav Moiseev

This paper presents near-optimal deterministic parallel and distributed algorithms for computing $(1+\varepsilon)$-approximate single-source shortest paths in any undirected weighted graph. On a high level, we deterministically reduce this…

Data Structures and Algorithms · Computer Science 2022-09-26 Václav Rozhoň , Christoph Grunau , Bernhard Haeupler , Goran Zuzic , Jason Li

Covariance matrix reconstruction is a topic of great significance in the field of one-bit signal processing and has numerous practical applications. Despite its importance, the conventional arcsine law with zero threshold is incapable of…

Signal Processing · Electrical Eng. & Systems 2023-03-30 Yu-Hang Xiao , Lei Huang , David Ramírez , Cheng Qian , Hing Cheung So

Given $n$ non-vertical lines in 3-space, their vertical depth (above/below) relation can contain cycles. We show that the lines can be cut into $O(n^{3/2}\mathop{\mathrm{polylog}} n)$ pieces, such that the depth relation among these pieces…

Computational Geometry · Computer Science 2016-06-09 Boris Aronov , Micha Sharir

We give improved algorithms for the $\ell_{p}$-regression problem, $\min_{x} \|x\|_{p}$ such that $A x=b,$ for all $p \in (1,2) \cup (2,\infty).$ Our algorithms obtain a high accuracy solution in $\tilde{O}_{p}(m^{\frac{|p-2|}{2p + |p-2|}})…

Data Structures and Algorithms · Computer Science 2024-12-20 Deeksha Adil , Rasmus Kyng , Richard Peng , Sushant Sachdeva

We consider linear stochastic bandits where the set of actions is an ellipsoid. We provide the first known minimax optimal algorithm for this problem. We first derive a novel information-theoretic lower bound on the regret of any algorithm,…

Machine Learning · Statistics 2025-02-25 Raymond Zhang , Hedi Hadiji , Richard Combes

Optimal transportation, or computing the Wasserstein or ``earth mover's'' distance between two distributions, is a fundamental primitive which arises in many learning and statistical settings. We give an algorithm which solves this problem…

Data Structures and Algorithms · Computer Science 2019-06-04 Arun Jambulapati , Aaron Sidford , Kevin Tian

We study high-dimensional mean estimation in a collaborative setting where data is contributed by $N$ users in batches of size $n$. In this environment, a learner seeks to recover the mean $\mu$ of a true distribution $P$ from a collection…

Machine Learning · Computer Science 2026-02-25 Maryam Aliakbarpour , Vladimir Braverman , Yuhan Liu , Junze Yin

In this paper, we present a new exact algorithm for counting perfect matchings, which relies on neither inclusion-exclusion principle nor tree-decompositions. For any bipartite graph of $2n$ nodes and $\Delta n$ edges such that $\Delta \geq…

Data Structures and Algorithms · Computer Science 2012-08-14 Taisuke Izumi , Tadashi Wadayama

This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements. We develop statistically and computationally efficient algorithms for the situation when the measurements…

Machine Learning · Statistics 2017-05-19 Huishuai Zhang , Yuejie Chi , Yingbin Liang

In this paper, we consider the "foreach" sparse recovery problem with failure probability $p$. The goal of which is to design a distribution over $m \times N$ matrices $\Phi$ and a decoding algorithm $\algo$ such that for every…

Data Structures and Algorithms · Computer Science 2013-04-24 Anna C. Gilbert , Hung Q. Ngo , Ely Porat , Atri Rudra , Martin J. Strauss

A common step in algorithms related to shortest paths in undirected graphs is that, we select a subset of vertices as centers, then grow a ball around each vertex until a center is reached. We want the balls to be as small as possible. A…

Data Structures and Algorithms · Computer Science 2025-10-15 Shuyi Yan

We consider a binary erasure version of the n-channel multiple descriptions problem with symmetric descriptions, i.e., the rates of the n descriptions are the same and the distortion constraint depends only on the number of messages…

Information Theory · Computer Science 2016-11-15 Ebad Ahmed , Aaron B. Wagner

We consider the problem of sketching the $p$-th frequency moment of a vector, $p>2$, with multiplicative error at most $1\pm \epsilon$ and \emph{with high confidence} $1-\delta$. Despite the long sequence of work on this problem, tight…

Data Structures and Algorithms · Computer Science 2018-05-29 Sumit Ganguly , David P. Woodruff