55 citations · 148 across the 14 of their papers we have counts for
8 papers · 1 filter
Quantum and Simulated Annealing-Based Iterative Algorithms for QUBO Relaxations of the Sparsest -Subgraph Problem
Omkar Bihani, Roman Kužel, Janez Povh +1
In this paper, we introduce three QUBO (Quadratic Unconstrained Binary Optimization) relaxations for the sparsest -subgraph (SkS) problem: a quadratic penalty relaxation, a Lagr…
Quantum computing and the stable set problem
Aljaž Krpan, Janez Povh, Dunja Pucher
Given an undirected graph, the stable set problem asks to determine the cardinality of the largest subset of pairwise non-adjacent vertices. This value is called the stability numb…
Advancing stable set problem solutions through quantum annealers
Janez Povh, Dunja Pucher
We assess the performance of D-wave quantum solvers for solving the stable set problem in a graph, one of the most studied NP-hard problems. We perform computations on some instanc…
Ground truth clustering is not the optimum clustering
Lucia Absalom Bautista, Timotej Hrga, Janez Povh +1
The clustering of data is one of the most important and challenging topics in data science. The minimum sum-of-squares clustering (MSSC) problem asks to cluster the data points int…
MADAM: A parallel exact solver for Max-Cut based on semidefinite programming and ADMM
Timotej Hrga, Janez Povh
We present MADAM, a parallel semidefinite based exact solver for Max-Cut, a problem of finding the cut with maximum weight in a given graph. The algorithm uses branch and bound par…
BiqBin: a parallel branch-and-bound solver for binary quadratic problems with linear constraints
Nicolò Gusmeroli, Timotej Hrga, Borut Lužar +3
We present BiqBin, an exact solver for linearly constrained binary quadratic problems. Our approach is based on an exact penalty method to first efficiently transform the original…
A Block Coordinate Descent-based Projected Gradient Algorithm for Orthogonal Non-negative Matrix Factorization
Soodabeh Asadi, Janez Povh
This article utilizes the projected gradient method (PG) for a non-negative matrix factorization problem (NMF), where one or both matrix factors must have orthonormal columns or ro…
Sparse Noncommutative Polynomial Optimization
Igor Klep, Victor Magron, Janez Povh
This article focuses on optimization of polynomials in noncommuting variables, while taking into account sparsity in the input data. A converging hierarchy of semidefinite relaxati…