27 citations · 47 across the 14 of their papers we have counts for
7 papers · 1 filter
APPA: Adaptive Preference Pluralistic Alignment for Fair Federated RLHF of LLMs
Mahmoud Srewa, Tianyu Zhao, Salma Elmalaki
Aligning large language models (LLMs) with diverse human preferences requires pluralistic alignment, where a single model must respect the values of multiple distinct groups simult…
PluralLLM: Pluralistic Alignment in LLMs via Federated Learning
Mahmoud Srewa, Tianyu Zhao, Salma Elmalaki
Ensuring Large Language Models (LLMs) align with diverse human preferences while preserving privacy and fairness remains a challenge. Existing methods, such as Reinforcement Learni…
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
Tianyu Zhao, Mahmoud Srewa, Salma Elmalaki
Federated Learning (FL) inherently mitigates mass data centralization risks; however, its privacy protections are not equally distributed - leaving vulnerable individuals dispropor…
PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning
Mojtaba Taherisadr, Salma Elmalaki
In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cloud services, exposing sensitive…
FAIRO: Fairness-aware Adaptation in Sequential-Decision Making for Human-in-the-Loop Systems
Tianyu Zhao, Mojtaba Taherisadr, Salma Elmalaki
Achieving fairness in sequential-decision making systems within Human-in-the-Loop (HITL) environments is a critical concern, especially when multiple humans with different behavior…
adaPARL: Adaptive Privacy-Aware Reinforcement Learning for Sequential-Decision Making Human-in-the-Loop Systems
Mojtaba Taherisadr, Stelios Andrew Stavroulakis, Salma Elmalaki
Reinforcement learning (RL) presents numerous benefits compared to rule-based approaches in various applications. Privacy concerns have grown with the widespread use of RL trained…
FaiR-IoT: Fairness-aware Human-in-the-Loop Reinforcement Learning for Harnessing Human Variability in Personalized IoT
Salma Elmalaki
Thanks to the rapid growth in wearable technologies, monitoring complex human context becomes feasible, paving the way to develop human-in-the-loop IoT systems that naturally evolv…