15 citations · 20 across the 10 of their papers we have counts for
12 papers
Robust Strategic Classification under Decision-Dependent Cost Uncertainty
Sura Alhanouti, Güzin Bayraksan, Parinaz Naghizadeh
Humans facing algorithmic decision systems have been found to ``game'' them by altering their input data (at a cost to them) in order to favorably change the algorithmic outcomes t…
Test-Time Adaptation for Unsupervised Combinatorial Optimization
Yiqiao Liao, Farinaz Koushanfar, Parinaz Naghizadeh
Unsupervised neural combinatorial optimization (NCO) enables learning powerful solvers without access to ground-truth solutions. Existing approaches fall into two disjoint paradigm…
Learning for Dynamic Combinatorial Optimization without Training Data
Yiqiao Liao, Farinaz Koushanfar, Parinaz Naghizadeh
We introduce DyCO-GNN, a novel unsupervised learning framework for Dynamic Combinatorial Optimization that requires no training data beyond the problem instance itself. DyCO-GNN le…
Anticipating Gaming to Incentivize Improvement: Guiding Agents in (Fair) Strategic Classification
Sura Alhanouti, Parinaz Naghizadeh
As machine learning algorithms increasingly influence critical decision making in different application areas, understanding human strategic behavior in response to these systems b…
The Feedback Loop Between Recommendation Systems and Reactive Users
Atefeh Mollabagher, Parinaz Naghizadeh
Recommendation systems underlie a variety of online platforms. These recommendation systems and their users form a feedback loop, wherein the former aims to maximize user engagemen…
Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria
Yiqiao Liao, Parinaz Naghizadeh
Although many fairness criteria have been proposed to ensure that machine learning algorithms do not exhibit or amplify our existing social biases, these algorithms are trained on…