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In this paper, we propose a new framework for designing fast parallel algorithms for fundamental statistical subset selection tasks that include feature selection and experimental design. Such tasks are known to be weakly submodular and are…

Machine Learning · Computer Science 2021-04-02 Sharon Qian , Yaron Singer

In the moldable job scheduling problem one has to assign a set of $n$ jobs to $m$ machines, in order to minimize the time it takes to process all jobs. Each job is moldable, so it can be assigned not only to one but any number of the equal…

Data Structures and Algorithms · Computer Science 2023-03-03 Kilian Grage , Klaus Jansen , Felix Ohnesorge

MAXCUT defines a classical NP-hard problem for graph partitioning and it serves as a typical case of the symmetric non-monotone Unconstrained Submodular Maximization (USM) problem. Applications of MAXCUT are abundant in machine learning,…

Data Structures and Algorithms · Computer Science 2016-09-06 Yatao Bian , Alexey Gronskiy , Joachim M. Buhmann

We propose a class of greedy algorithms for weighted sparse recovery by considering new loss function-based generalizations of Orthogonal Matching Pursuit (OMP). Given a (regularized) loss function, the proposed algorithms alternate the…

Information Theory · Computer Science 2025-02-18 Sina Mohammad-Taheri , Simone Brugiapaglia

Baswana, Gupta and Sen [FOCS'11] showed that fully dynamic maximal matching can be maintained in general graphs with logarithmic amortized update time. More specifically, starting from an empty graph on $n$ fixed vertices, they devised a…

Data Structures and Algorithms · Computer Science 2016-04-29 Shay Solomon

We study a core algorithmic problem in network design called ${F}$-augmentation that involves increasing the connectivity of a given family of cuts ${F}$. Over 30 years ago, Williamson et al. (STOC `93) provided a 2-approximation…

Data Structures and Algorithms · Computer Science 2025-04-10 Ishan Bansal

This paper addresses the problem of planning under uncertainty in large Markov Decision Processes (MDPs). Factored MDPs represent a complex state space using state variables and the transition model using a dynamic Bayesian network. This…

Artificial Intelligence · Computer Science 2011-06-10 C. Guestrin , D. Koller , R. Parr , S. Venkataraman

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem…

Data Structures and Algorithms · Computer Science 2015-12-08 Gabriele Fici , Tomasz Kociumaka , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń

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

An upper dominating set is a minimal dominating set in a graph. In the \textsc{Upper Dominating Set} problem, the goal is to find an upper dominating set of maximum size. We study the complexity of parameterized algorithms for \textsc{Upper…

Data Structures and Algorithms · Computer Science 2021-01-20 Louis Dublois , Michael Lampis , Vangelis Th. Paschos

We study the problem of maximizing a non-monotone submodular function under multiple knapsack constraints. We propose a simple discrete greedy algorithm to approach this problem, and prove that it yields strong approximation guarantees for…

Machine Learning · Computer Science 2020-02-19 Vanja Doskoč , Tobias Friedrich , Andreas Göbel , Frank Neumann , Aneta Neumann , Francesco Quinzan

Mobile agents have emerged as a powerful framework for solving fundamental graph problems in distributed settings in recent times. These agents, modelled as autonomous physical or software entities, possess local computation power, finite…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-26 Prabhat Kumar Chand , Anisur Rahaman Molla

As the scales of data sets expand rapidly in some application scenarios, increasing efforts have been made to develop fast submodular maximization algorithms. This paper presents a currently the most efficient algorithm for maximizing…

Data Structures and Algorithms · Computer Science 2018-11-20 Teng Li , Hyo-Sang Shin , Antonios Tsourdos

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 study the classic set cover problem from the perspective of sub-linear algorithms. Given access to a collection of $m$ sets over $n$ elements in the query model, we show that sub-linear algorithms derived from existing techniques have…

Data Structures and Algorithms · Computer Science 2019-02-12 Piotr Indyk , Sepideh Mahabadi , Ronitt Rubinfeld , Ali Vakilian , Anak Yodpinyanee

We study adaptive greedy algorithms for the problems of stochastic set cover with perfect and imperfect coverages. In stochastic set cover with perfect coverage, we are given a set of items and a ground set B. Evaluating an item reveals its…

Data Structures and Algorithms · Computer Science 2018-06-19 Srinivasan Parthasarathy

We present a technique that allows for improving on some relative greedy procedures by well-chosen (non-oblivious) local search algorithms. Relative greedy procedures are a particular type of greedy algorithm that start with a simple,…

Data Structures and Algorithms · Computer Science 2021-07-16 Vera Traub , Rico Zenklusen

A classic result of Williamson, Goemans, Mihail, and Vazirani [STOC 1993: 708-717] states that the problem of covering an uncrossable set family by a min-cost edge set admits approximation ratio $2$, by a primal-dual algorithm with a…

Data Structures and Algorithms · Computer Science 2025-05-27 Zeev Nutov

We consider two greedy algorithms for minimizing a convex function in a bounded convex set: an algorithm by Jones [1992] and the Frank-Wolfe (FW) algorithm. We first consider approximate versions of these algorithms. For smooth convex…

Optimization and Control · Mathematics 2018-11-19 Nan Ye , Peter Bartlett

In this paper, we study the non-monotone adaptive submodular maximization problem subject to a cardinality constraint. We first revisit the adaptive random greedy algorithm proposed in \citep{gotovos2015non}, where they show that this…

Machine Learning · Computer Science 2020-12-16 Shaojie Tang