19 citations · 19 across the 6 of their papers we have counts for
3 papers · 1 filter
Quantum Interior Point Methods: A Review of Developments and An Optimally Scaling Framework
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Pouya Sampourmahani +2
The growing demand for solving large-scale, data-intensive linear and conic optimization problems, particularly in applications such as artificial intelligence and machine learning…
Optimal Scaling Quantum Interior Point Method for Linear Optimization
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Pouya Sampourmahani +2
The emergence of huge-scale, data-intensive linear optimization (LO) problems in applications such as machine learning has driven the need for more computationally efficient interi…
An Efficient Quantum Algorithm for Linear System Problem in Tensor Format
Zeguan Wu, Sidhant Misra, Tamás Terlaky +2
Solving linear systems is at the foundation of many algorithms. Recently, quantum linear system algorithms (QLSAs) have attracted great attention since they converge to a solution…