Manish Raghavan

According to our database1, Manish Raghavan authored at least 32 papers between 2014 and 2024.

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Bibliography

2024
What Should We Do when Our Ideas of Fairness Conflict?
Commun. ACM, January, 2024

Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction.
CoRR, 2024

2023
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits.
SIAM J. Comput., April, 2023

Content Moderation and the Formation of Online Communities: A Theoretical Framework.
CoRR, 2023

Reconciling the accuracy-diversity trade-off in recommendations.
CoRR, 2023

Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection.
Proceedings of the ACM Web Conference 2023, 2023

Auditing for Human Expertise.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Societal Impacts of Algorithmic Decision-Making
ACM Books 53, ACM, ISBN: 979-8-4007-0862-6, 2023

2022
The Right to be an Exception to a Data-Driven Rule.
CoRR, 2022

The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Model Multiplicity: Opportunities, Concerns, and Solutions.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
The Societal Impacts of Algorithmic Decision-Making.
PhD thesis, 2021

Algorithmic monoculture and social welfare.
Proc. Natl. Acad. Sci. USA, 2021

Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems.
CoRR, 2021

Stochastic model for sunk cost bias.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020
How Do Classifiers Induce Agents to Invest Effort Strategically?
ACM Trans. Economics and Comput., 2020

Algorithmic classification and strategic effort.
SIGecom Exch., 2020

Mitigating bias in algorithmic hiring: evaluating claims and practices.
Proceedings of the FAT* '20: Conference on Fairness, 2020

The hidden assumptions behind counterfactual explanations and principal reasons.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Roles for computing in social change.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Designing Evaluation Rules That Are Robust to Strategic Behavior.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices.
CoRR, 2019

Hiring Under Uncertainty.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Mapping the Invocation Structure of Online Political Interaction.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Selection Problems in the Presence of Implicit Bias.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

The Externalities of Exploration and How Data Diversity Helps Exploitation.
Proceedings of the Conference On Learning Theory, 2018

2017
Planning with Multiple Biases.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

On Fairness and Calibration.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Inherent Trade-Offs in the Fair Determination of Risk Scores.
Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016
Planning Problems for Sophisticated Agents with Present Bias.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

2014
Deduplicating a places database.
Proceedings of the 23rd International World Wide Web Conference, 2014


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