Hoda Heidari

According to our database1, Hoda Heidari authored at least 34 papers between 2011 and 2022.

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Bibliography

2022
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms.
CoRR, 2022

Perspectives on Incorporating Expert Feedback into Model Updates.
CoRR, 2022

A Unifying Framework for Combining Complementary Strengths of Humans and ML toward Better Predictive Decision-Making.
CoRR, 2022

A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms.
CoRR, 2022

Allocating Opportunities in a Dynamic Model of Intergenerational Mobility (Extended Abstract).
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses.
Proceedings of the International Conference on Machine Learning, 2022

Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Bayesian Persuasion for Algorithmic Recourse.
CoRR, 2021

On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Stateful Strategic Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Addressing the Long-term Impact of ML Decisions via Policy Regret.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Allocating Opportunities in a Dynamic Model of Intergenerational Mobility.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Fair Equality of Chances for Prediction-based Decisions.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
On the Desiderata for Online Altruism: Nudging for Equitable Donations.
Proc. ACM Hum. Comput. Interact., 2020

2019
Competitive contagion in networks.
Games Econ. Behav., 2019

A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness.
CoRR, 2019

Economic Theories of Distributive Justice for Fair Machine Learning.
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

On the Impact of Choice Architectures on Inequality in Online Donation Platforms.
Proceedings of the World Wide Web Conference, 2019

Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets.
ACM Trans. Economics and Comput., 2018

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Preventing Disparate Treatment in Sequential Decision Making.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
A Convex Framework for Fair Regression.
CoRR, 2017

A General Framework for Evaluating Callout Mechanisms in Repeated Auctions.
CoRR, 2017

2016
Tight Policy Regret Bounds for Improving and Decaying Bandits.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Pricing a Low-regret Seller.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2014
Learning from Contagion (Without Timestamps).
Proceedings of the 31th International Conference on Machine Learning, 2014

New Models for Competitive Contagion.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Depth-Workload Tradeoffs for Workforce Organization.
Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

2011
Toward optimal vaccination strategies for probabilistic models.
Proceedings of the 20th International Conference on World Wide Web, 2011


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