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Graph partitioning aims to divide a graph into disjoint subsets while optimizing a specific partitioning objective. The majority of formulations related to graph partitioning exhibit NP-hardness due to their combinatorial nature.…

Machine Learning · Computer Science 2024-06-24 Rishi Shah , Krishnanshu Jain , Sahil Manchanda , Sourav Medya , Sayan Ranu

Given a connected undirected weighted graph, we are concerned with problems related to partitioning the graph. First of all we look for the closest disconnected graph (the minimum cut problem), here with respect to the Euclidean norm. We…

Numerical Analysis · Mathematics 2017-12-19 Eleonora Andreotti , Dominik Edelmann , Nicola Guglielmi , Christian Lubich

We study the fundamental problem of polytope membership aiming at large convex polytopes, i.e. in high dimension and with many facets, given as an intersection of halfspaces. Standard data-structures as well as brute force methods cannot…

Computational Geometry · Computer Science 2018-05-01 Evangelos Anagnostopoulos , Ioannis Z. Emiris , Vissarion Fisikopoulos

In this thesis, we settle the computational complexity of some fundamental questions in polynomial optimization. These include the questions of (i) finding a local minimum, (ii) testing local minimality of a point, and (iii) deciding…

Optimization and Control · Mathematics 2020-08-28 Jeffrey Zhang

We study the Minimum Crossing Number problem: given an $n$-vertex graph $G$, the goal is to find a drawing of $G$ in the plane with minimum number of edge crossings. This is one of the central problems in topological graph theory, that has…

Data Structures and Algorithms · Computer Science 2010-12-02 Julia Chuzhoy

We introduce the idea that the P vs NP problem can have a finer structure. Given the NP complete problem of interest, the configurations space of the problem can be divided in (at least) two regions. In one region, polynomial algorithms to…

Statistical Mechanics · Physics 2026-01-28 Fabrizio Canfora , Marco Cedeno

We establish the average-case hardness of the algorithmic problem of exact computation of the partition function associated with the Sherrington-Kirkpatrick model of spin glasses with Gaussian couplings and random external field. In…

Probability · Mathematics 2023-09-19 David Gamarnik , Eren Kizildag

Graph partitioning is the problem of dividing the nodes of a graph into balanced partitions while minimizing the edge cut across the partitions. Due to its combinatorial nature, many approximate solutions have been developed, including…

Machine Learning · Computer Science 2019-03-05 Azade Nazi , Will Hang , Anna Goldie , Sujith Ravi , Azalia Mirhoseini

We present a general method to convert algorithms into faster algorithms for almost-regular input instances. Informally, an almost-regular input is an input in which the maximum degree is larger than the average degree by at most a constant…

Data Structures and Algorithms · Computer Science 2022-11-22 Or Zamir

The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new…

Data Structures and Algorithms · Computer Science 2010-11-22 Manjish Pal

We consider the {\em Shaped Partition Problem} of partitioning $n$ given vectors in real $k$-space into $p$ parts so as to maximize an arbitrary objective function which is convex on the sum of vectors in each part, subject to arbitrary…

Combinatorics · Mathematics 2016-09-07 Frank K. Hwang , Shmuel Onn , Uriel G. Rothblum

Optimization is fundamental in many areas of science, from computer science and information theory to engineering and statistical physics, as well as to biology or social sciences. It typically involves a large number of variables and a…

Statistical Mechanics · Physics 2009-07-08 Lenka Zdeborová

One of the important unsolved problems in information theory is the conjecture that network coding has no rate benefit over routing in undirected unicast networks. Three known bounds on the symmetric rate in undirected unicast information…

Information Theory · Computer Science 2020-10-27 Mohammad Ishtiyaq Qureshi , Satyajit Thakor

We study a two-dimensional generalization of the classical Bin Packing problem, denoted as 2D Demand Bin Packing. In this context, each bin is a horizontal timeline, and rectangular tasks (representing electric appliances or computational…

Data Structures and Algorithms · Computer Science 2025-08-20 Susanne Albers , Waldo Gálvez , Ömer Behic Özdemir

We study the problem of computing the minimum adversarial perturbation of the Nearest Neighbor (NN) classifiers. Previous attempts either conduct attacks on continuous approximations of NN models or search for the perturbation by some…

Machine Learning · Computer Science 2019-06-11 Lu Wang , Xuanqing Liu , Jinfeng Yi , Zhi-Hua Zhou , Cho-Jui Hsieh

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping jobs based on their starting and ending times, that enable…

Data Structures and Algorithms · Computer Science 2023-02-27 Spencer Compton , Slobodan Mitrović , Ronitt Rubinfeld

We study the binary perceptron, a random constraint satisfaction problem that asks to find a Boolean vector in the intersection of independently chosen random halfspaces. A striking feature of this model is that at every positive constraint…

Computational Complexity · Computer Science 2026-04-02 Shuyang Gong , Brice Huang , Shuangping Li , Mark Sellke

Given a directed graph $G$ on $n$ vertices with a special vertex $s$, the directed minimum degree spanning tree problem requires computing a incoming spanning tree rooted at $s$ whose maximum tree in-degree is the smallest among all such…

Data Structures and Algorithms · Computer Science 2019-05-28 Ran Duan , Tianyi Zhang

Linear Programming (LP) is an important decoding technique for binary linear codes. However, the advantages of LP decoding, such as low error floor and strong theoretical guarantee, etc., come at the cost of high computational complexity…

Signal Processing · Electrical Eng. & Systems 2020-06-16 Yi Wei , Ming-Min Zhao , Min-Jian Zhao , Ming Lei

Molecular computing promises massive parallelization to explore solution spaces, but so far practical implementations remain limited due to off-target binding and exponential proliferation of competing structures. Here, we investigate the…

Soft Condensed Matter · Physics 2025-09-26 Erin Crawley , Qian-Ze Zhu , Michael P. Brenner
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