335 citations · 1.1k across the 63 of their papers we have counts for
11 papers · 1 filter
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…