PAC-Learning with General Class Noise Models. - Shahin Jabbari; Robert C. Holte; Sandra Zilles (KI, 2012)

Adaptive Task Assignment for Crowdsourced Classification. - Chien-Ju Ho; Shahin Jabbari; Jennifer Wortman Vaughan (ICML (1), 2013)

Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets. - Sepehr Assadi; Justin Hsu; Shahin Jabbari (HCOMP, 2015)

Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs. - Shahin Jabbari; Ryan M. Rogers; Aaron Roth 001; Zhiwei Steven Wu (NIPS, 2016)

Strategic Network Formation with Attack and Immunization. - Sanjeev Goyal; Shahin Jabbari; Michael J. Kearns; Sanjeev Khanna; Jamie Morgenstern (WINE, 2016)

Fair Learning in Markovian Environments. - Shahin Jabbari; Matthew Joseph; Michael J. Kearns; Jamie Morgenstern; Aaron Roth 001 (CoRR, 2016)

Fairness in Reinforcement Learning. - Shahin Jabbari; Matthew Joseph; Michael J. Kearns; Jamie Morgenstern; Aaron Roth 001 (ICML, 2017)

A Convex Framework for Fair Regression. - Richard Berk; Hoda Heidari; Shahin Jabbari; Matthew Joseph; Michael J. Kearns; Jamie Morgenstern; Seth Neel; Aaron Roth 001 (CoRR, 2017)

Fair Algorithms for Learning in Allocation Problems. - Hadi Elzayn; Shahin Jabbari; Christopher Jung 001; Michael J. Kearns; Seth Neel; Aaron Roth 001; Zachary Schutzman (FAT, 2019)

Network Formation under Random Attack and Probabilistic Spread. - Yu Chen 039; Shahin Jabbari; Michael J. Kearns; Sanjeev Khanna; Jamie Morgenstern (IJCAI, 2019)

Equilibrium Characterization for Data Acquisition Games. - Jinshuo Dong; Hadi Elzayn; Shahin Jabbari; Michael J. Kearns; Zachary Schutzman (IJCAI, 2019)

Robust Lock-Down Optimization for COVID-19 Policy Guidance. - Ankit Bhardwaj; Han-Ching Ou; Haipeng Chen 001; Shahin Jabbari; Milind Tambe; Rahul Panicker; Alpan Raval (AI4SG@AAAI Fall Symposium, 2020)

Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games. - Omkar Thakoor; Shahin Jabbari; Palvi Aggarwal; Cleotilde Gonzalez; Milind Tambe; Phebe Vayanos (GameSec, 2020)

Fair Influence Maximization: A Welfare Optimization Approach. - Aida Rahmattalabi; Shahin Jabbari; Himabindu Lakkaraju; Phebe Vayanos; Eric Rice; Milind Tambe (CoRR, 2020)

Fair Influence Maximization: a Welfare Optimization Approach. - Aida Rahmattalabi; Shahin Jabbari; Himabindu Lakkaraju; Phebe Vayanos; Max Izenberg; Ryan Brown; Eric Rice; Milind Tambe (AAAI, 2021)

Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. - Han-Ching Ou; Haipeng Chen 001; Shahin Jabbari; Milind Tambe (AAMAS, 2021)

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. - Sushant Agarwal; Shahin Jabbari; Chirag Agarwal; Sohini Upadhyay; Steven Wu 001; Himabindu Lakkaraju (ICML, 2021)

A Game-Theoretic Approach for Hierarchical Policy-Making. - Feiran Jia; Aditya Mate; Zun Li 002; Shahin Jabbari; Mithun Chakraborty; Milind Tambe; Michael P. Wellman; Yevgeniy Vorobeychik (CoRR, 2021)

Solving structured hierarchical games using differential backward induction. - Zun Li 002; Feiran Jia; Aditya Mate; Shahin Jabbari; Mithun Chakraborty; Milind Tambe; Yevgeniy Vorobeychik (UAI, 2022)

Designing effective masking strategies for cyberdefense through human experimentation and cognitive models. - Palvi Aggarwal; Omkar Thakoor; Shahin Jabbari; Edward A. Cranford; Christian Lebiere; Milind Tambe; Cleotilde Gonzalez (Comput. Secur., 2022)

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. - Satyapriya Krishna; Tessa Han; Alex Gu; Javin Pombra; Shahin Jabbari; Steven Wu 001; Himabindu Lakkaraju (CoRR, 2022)

TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments. - Vivek Khimani; Shahin Jabbari (CoRR, 2022)

Improving Fairness in Adaptive Social Exergames via Shapley Bandits. - Robert C. Gray; Jennifer Villareale; Thomas Boyd Fox; Diane H. Dallal; Santiago Ontañón; Danielle Arigo; Shahin Jabbari; Jichen Zhu (IUI, 2023)

The Evolving Meaning of Trust and Risk in Reddit Discourse about ChatGPT. - David Gefen; Shahin Jabbari; Rezvaneh (Shadi) Rezapour; Aria Pessianzadeh; Kshitij Kayastha; Hilde Van den Bulck (AMCIS, 2024)

Learning-Augmented Robust Algorithmic Recourse. - Kshitij Kayastha; Vasilis Gkatzelis; Shahin Jabbari (CoRR, 2024)

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. - Satyapriya Krishna; Tessa Han; Alex Gu; Steven Wu 001; Shahin Jabbari; Himabindu Lakkaraju (Trans. Mach. Learn. Res., 2024)

A game-theoretic approach for hierarchical epidemic control. - Feiran Jia; Aditya Mate; Zun Li 002; Shahin Jabbari; Mithun Chakraborty; Milind Tambe; Michael P. Wellman; Yevgeniy Vorobeychik (Auton. Agents Multi Agent Syst., 2025)