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While many solutions for privacy-preserving convex empirical risk minimization (ERM) have been developed, privacy-preserving nonconvex ERM remains a challenge. We study nonconvex ERM, which takes the form of minimizing a finite-sum of…

Machine Learning · Computer Science 2023-02-03 Lingxiao Wang , Bargav Jayaraman , David Evans , Quanquan Gu

Directed Steiner Tree (DST) is a central problem in combinatorial optimization and theoretical computer science: Given a directed graph $G=(V, E)$ with edge costs $c \in \mathbb{R}_{\geq 0}^E$, a root $r \in V$ and $k$ terminals $K\subseteq…

Data Structures and Algorithms · Computer Science 2020-04-28 Xiangyu Guo , Guy Kortsarz , Bundit Laekhanukit , Shi Li , Daniel Vaz , Jiayi Xian

We consider the minimax estimation problem of a discrete distribution with support size $k$ under privacy constraints. A privatization scheme is applied to each raw sample independently, and we need to estimate the distribution of the raw…

Machine Learning · Computer Science 2017-02-03 Min Ye , Alexander Barg

Some of the most fundamental and well-studied graph parameters are the Diameter (the largest shortest paths distance) and Radius (the smallest distance for which a "center" node can reach all other nodes). The natural and important…

Data Structures and Algorithms · Computer Science 2019-04-29 Mina Dalirrooyfard , Virginia Vassilevska Williams , Nikhil Vyas , Nicole Wein

The quadratic minimum spanning tree problem (QMSTP) is the problem of finding a spanning tree of a graph such that the total interaction cost between pairs of edges in the tree is minimized. We first show that most of the bounding…

Optimization and Control · Mathematics 2024-04-09 Renata Sotirov , Zoe Verchére

In this work we consider the Metric Steiner Forest problem in the sublinear time model. Given a set $V$ of $n$ points in a metric space where distances are provided by means of query access to an $n\times n$ distance matrix, along with a…

Data Structures and Algorithms · Computer Science 2025-10-14 Sepideh Mahabadi , Mohammad Roghani , Jakub Tarnawski , Ali Vakilian

In this paper we describe an algorithm that embeds a graph metric $(V,d_G)$ on an undirected weighted graph $G=(V,E)$ into a distribution of tree metrics $(T,D_T)$ such that for every pair $u,v\in V$, $d_G(u,v)\leq d_T(u,v)$ and…

Data Structures and Algorithms · Computer Science 2017-05-29 Guy E. Blelloch , Yan Gu , Yihan Sun

We present a family of fast pseudo-approximation algorithms for the minimum balanced vertex separator problem in a graph. Given a graph $G=(V,E)$ with $n$ vertices and $m$ edges, and a (constant) balance parameter $c\in(0,1/2)$, where $G$…

Data Structures and Algorithms · Computer Science 2026-03-18 Vladimir Kolmogorov , Jack Spalding-Jamieson

The Angular Constrained Minimum Spanning Tree Problem ($\alpha$-MSTP) is defined in terms of a complete undirected graph $G=(V,E)$ and an angle $\alpha \in (0,2\pi]$. Vertices of $G$ define points in the Euclidean plane while edges, the…

Optimization and Control · Mathematics 2020-05-26 Alexandre Salles da Cunha

We study the classic Euclidean Minimum Spanning Tree (MST) problem in the Massively Parallel Computation (MPC) model. Given a set $X \subset \mathbb{R}^d$ of $n$ points, the goal is to produce a spanning tree for $X$ with weight within a…

Data Structures and Algorithms · Computer Science 2023-08-02 Rajesh Jayaram , Vahab Mirrokni , Shyam Narayanan , Peilin Zhong

The seminal work of Ahn, Guha, and McGregor in 2012 introduced the graph sketching technique and used it to present the first streaming algorithms for various graph problems over dynamic streams with both insertions and deletions of edges.…

Data Structures and Algorithms · Computer Science 2023-12-11 Sepehr Assadi , Gillat Kol , Zhijun Zhang

We study differentially private stochastic optimization in convex and non-convex settings. For the convex case, we focus on the family of non-smooth generalized linear losses (GLLs). Our algorithm for the $\ell_2$ setting achieves optimal…

Machine Learning · Computer Science 2021-11-11 Raef Bassily , Cristóbal Guzmán , Michael Menart

We consider the problem of differentially private (DP) convex empirical risk minimization (ERM). While the standard DP-SGD algorithm is theoretically well-established, practical implementations often rely on shuffled gradient methods that…

Machine Learning · Computer Science 2026-02-25 Shuli Jiang , Pranay Sharma , Zhiwei Steven Wu , Gauri Joshi

We present a deterministic algorithm for computing the sensitivity of a minimum spanning tree (MST) or shortest path tree in $O(m\log\alpha(m,n))$ time, where $\alpha$ is the inverse-Ackermann function. This improves upon a long standing…

Data Structures and Algorithms · Computer Science 2014-07-09 Seth Pettie

We propose differentially private algorithms for parameter estimation in both low-dimensional and high-dimensional sparse generalized linear models (GLMs) by constructing private versions of projected gradient descent. We show that the…

Machine Learning · Statistics 2020-12-08 T. Tony Cai , Yichen Wang , Linjun Zhang

We prove that the local limit of the weighted spanning trees on any simple connected high degree almost regular sequence of electric networks is the Poisson(1) branching process conditioned to survive forever, by generalizing [NP22] and…

Probability · Mathematics 2026-01-01 Ágnes Kúsz

We initiate a systematic study of worst-group risk minimization under $(\epsilon, \delta)$-differential privacy (DP). The goal is to privately find a model that approximately minimizes the maximal risk across $p$ sub-populations (groups)…

Machine Learning · Computer Science 2024-03-01 Xinyu Zhou , Raef Bassily

We prove that Simulated Annealing with an appropriate cooling schedule computes arbitrarily tight constant-factor approximations to the minimum spanning tree problem in polynomial time. This result was conjectured by Wegener (2005). More…

Neural and Evolutionary Computing · Computer Science 2023-07-25 Benjamin Doerr , Amirhossein Rajabi , Carsten Witt

Constructing the maximum spanning tree $T$ of an edge-weighted connected graph $G$ is one of the important research topics in computer science and optimization, and the related research results have played an active role in practical…

Combinatorics · Mathematics 2024-12-30 Hui Lei , Mei Lu , Yongtang Shi , Jian Sun , Xiamiao Zhao

Computing the Euclidean minimum spanning tree (EMST) is a computationally demanding step of many algorithms. While work-efficient serial and multithreaded algorithms for computing EMST are known, designing an efficient GPU algorithm is…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-08 Andrey Prokopenko , Piyush Sao , Damien Lebrun-Grandié
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