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Over the last two decades, submodular function maximization has been the workhorse of many discrete optimization problems in machine learning applications. Traditionally, the study of submodular functions was based on binary function…

Machine Learning · Computer Science 2022-05-18 Loay Mualem , Moran Feldman

We study \emph{sublinear} algorithms that solve linear systems locally. In the classical version of this problem the input is a matrix $S\in \mathbb{R}^{n\times n}$ and a vector $b\in\mathbb{R}^n$ in the range of $S$, and the goal is to…

Data Structures and Algorithms · Computer Science 2026-02-23 Alexandr Andoni , Robert Krauthgamer , Yosef Pogrow

In this paper, we introduce a novel technique for constrained submodular maximization, inspired by barrier functions in continuous optimization. This connection not only improves the running time for constrained submodular maximization but…

Machine Learning · Computer Science 2020-02-11 Ashwinkumar Badanidiyuru , Amin Karbasi , Ehsan Kazemi , Jan Vondrak

Submodular functions are set functions mapping every subset of some ground set of size $n$ into the real numbers and satisfying the diminishing returns property. Submodular minimization is an important field in discrete optimization theory…

Data Structures and Algorithms · Computer Science 2020-01-16 Yassine Hamoudi , Patrick Rebentrost , Ansis Rosmanis , Miklos Santha

First, for the for the submodular $k$-secretary problem with shortlists [1], we provide a near optimal $1-1/e-\epsilon$ approximation using shortlist of size $O(k poly(1/\epsilon))$. In particular, we improve the size of shortlist used in…

Data Structures and Algorithms · Computer Science 2021-02-22 Mohammad Shadravan

We study the complexity of approximate representation and learning of submodular functions over the uniform distribution on the Boolean hypercube $\{0,1\}^n$. Our main result is the following structural theorem: any submodular function is…

Machine Learning · Computer Science 2013-04-03 Vitaly Feldman , Pravesh Kothari , Jan Vondrak

Finding dense subgraphs of a large graph is a standard problem in graph mining that has been studied extensively both for its theoretical richness and its many practical applications. In this paper we introduce a new family of dense…

Data Structures and Algorithms · Computer Science 2021-06-07 Nate Veldt , Austin R. Benson , Jon Kleinberg

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

The partition problem is a well-known basic NP-complete problem. We mainly consider the optimization version of it in this paper. The problem has been investigated from various perspectives for a long time and can be solved efficiently in…

Discrete Mathematics · Computer Science 2024-05-10 Susumu Kubo

We introduce a new combinatorial structure: the superselector. We show that superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel…

Data Structures and Algorithms · Computer Science 2010-10-07 Ferdinando Cicalese , Ugo Vaccaro

It is well known that, whenever $k$ divides $n$, the complete $k$-uniform hypergraph on $n$ vertices can be partitioned into disjoint perfect matchings. Equivalently, the set of $k$-subsets of an $n$-set can be partitioned into parallel…

Combinatorics · Mathematics 2020-07-24 Yeow Meng Chee , Tuvi Etzion , Han Mao Kiah , Alexander Vardy , Chengmin Wang

We consider the following two deterministic inventory optimization problems over a finite planning horizon $T$ with non-stationary demands. (a) Submodular Joint Replenishment Problem: This involves multiple item types and a single retailer…

Data Structures and Algorithms · Computer Science 2015-04-27 Viswanath Nagarajan , Cong Shi

We revisit two NP-hard geometric partitioning problems - convex decomposition and surface approximation. Building on recent developments in geometric separators, we present quasi-polynomial time algorithms for these problems with improved…

Computational Geometry · Computer Science 2014-04-16 Sayan Bandyapadhyay , Santanu Bhowmick , Kasturi Varadarajan

Given $(a_1, \dots, a_n, t) \in \mathbb{Z}_{\geq 0}^{n + 1}$, the Subset Sum problem ($\mathsf{SSUM}$) is to decide whether there exists $S \subseteq [n]$ such that $\sum_{i \in S} a_i = t$. There is a close variant of the $\mathsf{SSUM}$,…

Data Structures and Algorithms · Computer Science 2022-06-02 Pranjal Dutta , Mahesh Sreekumar Rajasree

In recent years we have witnessed an increase on the development of methods for submodular optimization, which have been motivated by the wide applicability of submodular functions in real-world data-science problems. In this paper, we…

Data Structures and Algorithms · Computer Science 2022-09-15 Guangyi Zhang , Nikolaj Tatti , Aristides Gionis

Our overall goal is to unify and extend some results in the literature related to the approximation of generating functions of finite and infinite sequences over a field by rational functions. In our approach, numerators play a significant…

Symbolic Computation · Computer Science 2015-04-08 Graham H. Norton

In the $(k,m)$-mappability problem, for a given sequence $T$ of length $n$, the goal is to compute a table whose $i$th entry is the number of indices $j \ne i$ such that the length-$m$ substrings of $T$ starting at positions $i$ and $j$…

Data Structures and Algorithms · Computer Science 2021-06-18 Panagiotis Charalampopoulos , Costas S. Iliopoulos , Tomasz Kociumaka , Solon P. Pissis , Jakub Radoszewski , Juliusz Straszyński

We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem…

Computational Complexity · Computer Science 2013-01-07 Adam Klivans , Raghu Meka

We consider the problem of solving the Min-Sum Submodular Cover problem using local search. The Min-Sum Submodular Cover problem generalizes the NP-complete Min-Sum Set Cover problem, replacing the input set cover instance with a monotone…

Data Structures and Algorithms · Computer Science 2023-12-05 Lisa Hellerstein , Thomas Lidbetter , R. Teal Witter

In a stochastic probing problem we are given a universe $E$, where each element $e \in E$ is active independently with probability $p_e$, and only a probe of e can tell us whether it is active or not. On this universe we execute a process…

Data Structures and Algorithms · Computer Science 2014-02-19 Marek Adamczyk , Maxim Sviridenko , Justin Ward
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