9 citations · 9 across the 7 of their papers we have counts for
7 papers
Sparse plus low-rank matrix embedding with applications in cancer radiotherapy optimization
Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh
Decomposing a matrix into sparse and low-rank components is central to robust principal component analysis and has broad applications in machine learning, signal processing, and co…
Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning
Mahdi Salahshour, Amirahmad Shafiee, Mojtaba Tefagh
The Lightning Network (LN) has emerged as a second-layer solution to Bitcoin's scalability challenges. The rise of Payment Channel Networks (PCNs) and their specific mechanisms inc…
Compressed radiotherapy treatment planning (CompressRTP): A new paradigm for rapid and high-quality treatment planning optimization
Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh
Background: Radiotherapy treatment planning involves solving large-scale optimization problems that are often approximated and solved sub-optimally due to time constraints. Central…
DyFEn: Agent-Based Fee Setting in Payment Channel Networks
Kiana Asgari, Aida Afshar Mohammadian, Mojtaba Tefagh
In recent years, with the development of easy to use learning environments, implementing and reproducible benchmarking of reinforcement learning algorithms has been largely acceler…
Multi-Feasibility Variable Selection
Ali Fathi, Mohammad Rashid, Shayan Ranjbarzadeh +1
This paper is the report of the problem proposed for the !Optimizer 2021 competition, and the solutions of the gold medalist team, i.e., the Panda team. The competition was held in…
A Highly Symmetric Hamilton Decomposition for Hypercubes
Farid Bouya, Ebadollah S. Mahmoodian, Modjtaba Shokrian Zini +1
A Hamilton decomposition of a graph is a partitioning of its edge set into disjoint spanning cycles. The existence of such decompositions is known for all hypercubes of even dimens…