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Setcover greedy algorithm is a natural approximation algorithm for test set problem. This paper gives a precise and tighter analysis of performance guarantee of this algorithm. The author improves the performance guarantee $2\ln n$ which…

Data Structures and Algorithms · Computer Science 2011-03-08 Peng Cui

$\newcommand{\eps}{\varepsilon}$ In this paper, we consider two important problems defined on finite metric spaces, and provide efficient new algorithms and approximation schemes for these problems on inputs given as graph shortest path…

Computational Geometry · Computer Science 2021-02-23 David Eppstein , Sariel Har-Peled , Anastasios Sidiropoulos

Identifying breakpoints in piecewise regression is critical in enhancing the reliability and interpretability of data fitting. In this paper, we propose novel algorithms based on the greedy algorithm to accurately and efficiently identify…

Machine Learning · Statistics 2026-04-14 Taehyeong Kim , Hyungu Lee , Myungjin Kim , Hayoung Choi

In the dynamic set cover problem, the input is a dynamic universe of elements and a fixed collection of sets. As elements are inserted or deleted, the goal is to efficiently maintain an approximate minimum set cover. While the past decade…

Data Structures and Algorithms · Computer Science 2026-04-06 Amitai Uzrad

A $k$-submodular function naturally generalizes submodular functions by taking as input $k$ disjoint subsets, rather than a single subset. Unlike standard submodular maximization, which only requires selecting elements for the solution,…

Data Structures and Algorithms · Computer Science 2025-07-18 Chenhao Wang

The greedy algorithm adapted from Kruskal's algorithm is an efficient and folklore way to produce a $k$-spanner with girth at least $k+2$. The greedy algorithm has shown to be `existentially optimal', while it's not `universally optimal'…

Data Structures and Algorithms · Computer Science 2024-11-05 Yeyuan Chen

In any attempt at designing an efficient algorithm for the minimum vertex cover problem, obtaining good upper and lower bounds for the vertex cover number could be crucial. In this article we present a modified greedy algorithm of…

Combinatorics · Mathematics 2019-01-04 R. Dharmarajan , D. Ramachandran

An effective technique for solving optimization problems over massive data sets is to partition the data into smaller pieces, solve the problem on each piece and compute a representative solution from it, and finally obtain a solution…

Data Structures and Algorithms · Computer Science 2015-06-23 Vahab Mirrokni , Morteza Zadimoghaddam

In the problem of online unweighted interval selection, the objective is to maximize the number of non-conflicting intervals accepted by the algorithm. In the conventional online model of irrevocable decisions, there is an Omega(n) lower…

Data Structures and Algorithms · Computer Science 2025-06-03 Allan Borodin , Christodoulos Karavasilis

We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the context of both feature selection and sparse…

Machine Learning · Statistics 2011-02-28 Abhimanyu Das , David Kempe

Given a set of $n$ vectors in $\mathbb{R}^d$, the goal of the \emph{determinant maximization} problem is to pick $k$ vectors with the maximum volume. Determinant maximization is the MAP-inference task for determinantal point processes (DPP)…

Data Structures and Algorithms · Computer Science 2023-09-28 Siddharth Gollapudi , Sepideh Mahabadi , Varun Sivashankar

We consider single-machine scheduling problems that are natural generalizations or variations of the min-sum set cover problem and the min-sum vertex cover problem. For each of these problems, we give new approximation algorithms. Some of…

Data Structures and Algorithms · Computer Science 2020-01-22 Felix Happach , Andreas S. Schulz

The dynamic set cover problem has been subject to growing research attention in recent years. In this problem, we are given as input a dynamic universe of at most $n$ elements and a fixed collection of $m$ sets, where each element appears…

Data Structures and Algorithms · Computer Science 2024-07-10 Shay Solomon , Amitai Uzrad , Tianyi Zhang

The submodular maximization problem is widely applicable in many engineering problems where objectives exhibit diminishing returns. While this problem is known to be NP-hard for certain subclasses of objective functions, there is a greedy…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-01 Haoyuan Sun , David Grimsman , Jason R Marden

Many important problems in discrete optimization require maximization of a monotonic submodular function subject to matroid constraints. For these problems, a simple greedy algorithm is guaranteed to obtain near-optimal solutions. In this…

Data Structures and Algorithms · Computer Science 2015-03-17 Daniel Golovin , Andreas Krause

We consider interactive learning and covering problems, in a setting where actions may incur different costs, depending on the response to the action. We propose a natural greedy algorithm for response-dependent costs. We bound the…

Machine Learning · Computer Science 2018-11-21 Sivan Sabato

We assume the permutation $\pi$ is given by an $n$-element array in which the $i$-th element denotes the value $\pi(i)$. Constructing its inverse in-place (i.e. using $O(\log{n})$ bits of additional memory) can be achieved in linear time…

Data Structures and Algorithms · Computer Science 2020-04-22 Grzegorz Guśpiel

Previous compact representations of permutations have focused on adding a small index on top of the plain data $<\pi(1), \pi(2),...\pi(n)>$, in order to efficiently support the application of the inverse or the iterated permutation. In this…

Data Structures and Algorithms · Computer Science 2011-08-23 Jérémy Barbay , Gonzalo Navarro

We study the approximability of the maximum size independent set (MIS) problem in bounded degree graphs. This is one of the most classic and widely studied NP-hard optimization problems. We focus on the well known minimum degree greedy…

Data Structures and Algorithms · Computer Science 2020-02-03 Piotr Krysta , Mathieu Mari , Nan Zhi

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi