Shahin Jabbari

According to our database, Shahin Jabbari authored at least 26 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju

Trans. Mach. Learn. Res., 2024

Learning-Augmented Robust Algorithmic Recourse.

Kshitij Kayastha, Vasilis Gkatzelis, Shahin Jabbari

CoRR, 2024

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

Proceedings of the 30th Americas Conference on Information Systems: Elevating Life through Digital Social Entrepreneurship, 2024

2023

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

Proceedings of the 28th International Conference on Intelligent User Interfaces, 2023

2022

TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments.

Vivek Khimani, Shahin Jabbari

CoRR, 2022

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, Himabindu Lakkaraju

CoRR, 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

Solving structured hierarchical games using differential backward induction.

Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

A Game-Theoretic Approach for Hierarchical Policy-Making.

Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik

CoRR, 2021

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations.

Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju

Proceedings of the 38th International Conference on Machine Learning, 2021

Active Screening for Recurrent Diseases: A Reinforcement Learning Approach.

Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Fair Influence Maximization: a Welfare Optimization Approach.

Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Fair Influence Maximization: A Welfare Optimization Approach.

Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Eric Rice, Milind Tambe

CoRR, 2020

Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games.

Omkar Thakoor, Shahin Jabbari, Palvi Aggarwal, Cleotilde Gonzalez, Milind Tambe, Phebe Vayanos

Proceedings of the Decision and Game Theory for Security - 11th International Conference, 2020

Robust Lock-Down Optimization for COVID-19 Policy Guidance.

Ankit Bhardwaj, Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe, Rahul Panicker, Alpan Raval

Proceedings of the AAAI Fall Symposium on AI for Social Good, 2020

2019

Equilibrium Characterization for Data Acquisition Games.

Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael J. Kearns, Zachary Schutzman

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Network Formation under Random Attack and Probabilistic Spread.

Yu Chen, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Fair Algorithms for Learning in Allocation Problems.

Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2017

A Convex Framework for Fair Regression.

Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, Aaron Roth

CoRR, 2017

Fairness in Reinforcement Learning.

Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Aaron Roth

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Fair Learning in Markovian Environments.

Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Aaron Roth

CoRR, 2016

Strategic Network Formation with Attack and Immunization.

Sanjeev Goyal, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern

Proceedings of the Web and Internet Economics - 12th International Conference, 2016

Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs.

Shahin Jabbari, Ryan M. Rogers, Aaron Roth, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets.

Sepehr Assadi, Justin Hsu, Shahin Jabbari

Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

2013

Adaptive Task Assignment for Crowdsourced Classification.

Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

PAC-Learning with General Class Noise Models.

Shahin Jabbari, Robert C. Holte, Sandra Zilles

Proceedings of the KI 2012: Advances in Artificial Intelligence, 2012