335 citations · 1.1k across the 63 of their papers we have counts for
65 papers
Guiding Agents of Quantum Games to Equilibrium using Matrix Exponential Fixed-Point Iteration
Alireza Habibi, Luis F. Abanto Leon, Setareh Maghsudi
In recent years, quantum game theory has gained significant attention as a framework for studying decision-making in multi-agent systems using quantum principles. However, computin…
Riemannian Optimization for Multi-Player Quantum Games on Product Unitary Manifolds
Alireza Habibi, Setareh Maghsudi
Quantum game theory is an extension of classical game theory that uses quantum principles in game theory. The Eisert-Wilkens-Lewenstein (EWL) quantum game is an early example of th…
Graph Structured Combinatorial Semi-Bandit with Nonlinear Reward Associations through Separable Signals
Christoph Bauschmann, Setareh Maghsudi
The identification of optimal structures within vast arrays of interconnected data necessitates significant sampling- and computational effort. Learning and leveraging underlying s…
One Model for All: Multi-Objective Controllable Language Models
Qiang He, Yucheng Yang, Tianyi Zhou +3
Aligning large language models (LLMs) with human preferences is critical for enhancing LLMs' safety, helpfulness, humor, faithfulness, etc. Current reinforcement learning from huma…
Robust Optimization Approach and Learning Based Hide-and-Seek Game for Resilient Network Design
Mohammad Khosravi, Setareh Maghsudi
We study the design of resilient and reliable communication networks in which a signal can be transferred only up to a limited distance before its quality falls below an acceptable…
A Robust Optimization Approach for Regenerator Placement in Fault-Tolerant Networks Under Discrete Cost Uncertainty
Mohammad Khosravi, Setareh Maghsudi
We focus on robust, survivable communication networks, where network links and nodes are affected by an uncertainty set. In this sense, any network links might fail. Besides, a sig…
Generation of Programmatic Rules for Document Forgery Detection Using Large Language Models
Valentin Schmidberger, Manuel Eberhardinger, Setareh Maghsudi +1
Document forgery poses a growing threat to legal, economic, and governmental processes, requiring increasingly sophisticated verification mechanisms. One approach involves the use…
Meta-Learning Multi-armed Bandits for Beam Tracking in 5G and 6G Networks
Alexander Mattick, George Yammine, Georgios Kontes +2
Beamforming-capable antenna arrays with many elements enable higher data rates in next generation 5G and 6G networks. In current practice, analog beamforming uses a codebook of pre…
Resilient Full-Duplex ISAC in the Face of Imperfect SI Cancellation: Globally Optimal Timeslot Allocation and Beam Selection
Luis F. Abanto-Leon, Setareh Maghsudi
This work addresses the radio resource management (RRM) design in downlink full-duplex integrated sensing and communications (ISAC) systems, jointly optimizing timeslot allocation…
Anomaly Detection in Networked Bandits
Xiaotong Cheng, Setareh Maghsudi
The nodes' interconnections on a social network often reflect their dependencies and information-sharing behaviors. Nevertheless, abnormal nodes, which significantly deviate from m…
Pareto Multi-Objective Alignment for Language Models
Qiang He, Setareh Maghsudi
Large language models (LLMs) are increasingly deployed in real-world applications that require careful balancing of multiple, often conflicting, objectives, such as informativeness…
Emergence of Fair Leaders via Mediators in Multi-Agent Reinforcement Learning
Akshay Dodwadmath, Setareh Maghsudi
Stackelberg games and their resulting equilibria have received increasing attention in the multi-agent reinforcement learning literature. Each stage of a traditional Stackelberg ga…
Efficient Resource Allocation under Adversary Attacks: A Decomposition-Based Approach
Mansoor Davoodi, Setareh Maghsudi
We address the problem of allocating limited resources in a network under persistent yet statistically unknown adversarial attacks. Each node in the network may be degraded, but no…
Stochastic Multi-Objective Multi-Armed Bandits: Regret Definition and Algorithm
Mansoor Davoodi, Setareh Maghsudi
Multi-armed bandit (MAB) problems are widely applied to online optimization tasks that require balancing exploration and exploitation. In practical scenarios, these tasks often inv…
Service Placement in Small Cell Networks Using Distributed Best Arm Identification in Linear Bandits
Mariam Yahya, Aydin Sezgin, Setareh Maghsudi
As users in small cell networks increasingly rely on computation-intensive services, cloud-based access often results in high latency. Multi-access edge computing (MEC) mitigates t…
Quantum-Inspired Reinforcement Learning in the Presence of Epistemic Ambivalence
Alireza Habibi, Saeed Ghoorchian, Setareh Maghsudi
The complexity of online decision-making under uncertainty stems from the requirement of finding a balance between exploiting known strategies and exploring new possibilities. Natu…
Optimal User and Target Scheduling, User-Target Pairing, and Low-Resolution Phase-Only Beamforming for ISAC Systems
Luis F. Abanto-Leon, Setareh Maghsudi
We investigate the joint user and target scheduling, user-target pairing, and low-resolution phase-only beamforming design for integrated sensing and communications (ISAC). Schedul…
Hierarchical Functionality Prioritization in Multicast ISAC: Optimal Admission Control and Discrete-Phase Beamforming
Luis F. Abanto-Leon, Setareh Maghsudi
We investigate the joint admission control and discrete-phase multicast beamforming design for integrated sensing and communications (ISAC) systems, where sensing and communication…
From Code to Play: Benchmarking Program Search for Games Using Large Language Models
Manuel Eberhardinger, James Goodman, Alexander Dockhorn +5
Large language models (LLMs) have shown impressive capabilities in generating program code, opening exciting opportunities for applying program synthesis to games. In this work, we…
Online Influence Maximization with Semi-Bandit Feedback under Corruptions
Xiaotong Cheng, Behzad Nourani-Koliji, Setareh Maghsudi
In this work, we investigate the online influence maximization in social networks. Most prior research studies on online influence maximization assume that the nodes are fully coop…
Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming
Manuel Eberhardinger, Florian Rupp, Johannes Maucher +1
Despite tremendous progress, machine learning and deep learning still suffer from incomprehensible predictions. Incomprehensibility, however, is not an option for the use of (deep)…
Decentralized Task Offloading and Load-Balancing for Mobile Edge Computing in Dense Networks
Mariam Yahya, Alexander Conzelmann, Setareh Maghsudi
We study the problem of decentralized task offloading and load-balancing in a dense network with numerous devices and a set of edge servers. Solving this problem optimally is compl…
Distributed Management of Fluctuating Energy Resources in Dynamic Networked Systems
Xiaotong Cheng, Ioannis Tsetis, Setareh Maghsudi
Modern power systems integrate renewable distributed energy resources (DERs) as an environment-friendly enhancement to meet the ever-increasing demands. However, the inherent unrel…
Budgeted Recommendation with Delayed Feedback
Kweiguu Liu, Setareh Maghsudi
In a conventional contextual multi-armed bandit problem, the feedback (or reward) is immediately observable after an action. Nevertheless, delayed feedback arises in numerous real-…