7 papers
Decision-Focused Learning in Network Interdiction Games
Luca M. Hartmann, Parinaz Naghizadeh
We study decision-focused learning (DFL) in shortest-path network interdiction (SPNI) games, a Stackelberg game where an interdictor (leader) strengthens the networks' arcs against…
Rethinking Learning-Based Influence Maximization: Simple Neural Surrogates and Native Discrete Search
Yiqiao Liao, Parinaz Naghizadeh
Existing learning-based influence maximization frameworks rely heavily on complex neural architectures and continuous optimization over seed representations. We challenge this para…
Reactive Users vs. Social Recommender Systems: Managing Opinion Drifts with Adaptive Policies
Atefeh Mollabagher, Parinaz Naghizadeh
Recommendation systems are used in a range of platforms to maximize user engagement through personalization, promotion of popular content, and the use of information from social ne…
Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering
Yifan Yang, Ali Payani, Parinaz Naghizadeh
Federated Learning (FL) has been a pivotal paradigm for collaborative training of machine learning models across distributed datasets. In heterogeneous settings, it has been observ…
United We Fall: On the Nash Equilibria of Multiplex and Multilayer Network Games
Raman Ebrahimi, Parinaz Naghizadeh
Network games provide a framework to study strategic decision making processes that are governed by structured interdependencies among agents. However, existing models do not accou…
An advantage based policy transfer algorithm for reinforcement learning with measures of transferability
Md Ferdous Alam, Parinaz Naghizadeh, David Hoelzle
Reinforcement learning (RL) enables sequential decision-making in complex and high-dimensional environments through interaction with the environment. In most real-world application…