Manish Raghavan

According to our database, Manish Raghavan authored at least 37 papers between 2014 and 2024.

Collaborative distances:

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

2024

What Should We Do when Our Ideas of Fairness Conflict?

Manish Raghavan

Commun. ACM, January, 2024

Competition and Diversity in Generative AI.

Manish Raghavan

CoRR, 2024

Integrating Expert Judgment and Algorithmic Decision Making: An Indistinguishability Framework.

Rohan Alur, Loren Laine, Darrick K. Li, Dennis L. Shung, Manish Raghavan, Devavrat Shah

CoRR, 2024

Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models.

Vinith M. Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson

CoRR, 2024

Synthetic Census Data Generation via Multidimensional Multiset Sum.

Cynthia Dwork, Kristjan H. Greenewald, Manish Raghavan

CoRR, 2024

Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction.

Rohan Alur, Manish Raghavan, Devavrat Shah

CoRR, 2024

Reconciling the Accuracy-Diversity Trade-off in Recommendations.

Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg

Proceedings of the ACM on Web Conference 2024, 2024

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

Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan

Proceedings of the ACM on Web Conference 2024, 2024

Equilibria, Efficiency, and Inequality in Network Formation for Hiring and Opportunity.

Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan

Proceedings of the 25th ACM Conference on Economics and Computation, 2024

2023

Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits.

Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu

SIAM J. Comput., April, 2023

Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection.

Chris Hays, Zachary Schutzman, Manish Raghavan, Erin Walk, Philipp Zimmer

Proceedings of the ACM Web Conference 2023, 2023

Auditing for Human Expertise.

Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung

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

Manish Raghavan

ACM Books 53, ACM, ISBN: 979-8-4007-0862-6, 2023

2022

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

Sarah H. Cen, Manish Raghavan

CoRR, 2022

The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization.

Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan

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.

Emily Black, Manish Raghavan, Solon Barocas

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.

Manish Raghavan

PhD thesis, 2021

Algorithmic monoculture and social welfare.

Jon M. Kleinberg, Manish Raghavan

Proc. Natl. Acad. Sci. USA, 2021

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

Chloé Bakalar, Renata Barreto, Stevie Bergman, Miranda Bogen, Bobbie Chern, Sam Corbett-Davies, Melissa Hall, Isabel Kloumann, Michelle Lam, Joaquin Quiñonero Candela, Manish Raghavan, Joshua Simons, Jonathan Tannen, Edmund Tong, Kate Vredenburgh, Jiejing Zhao

CoRR, 2021

Stochastic model for sunk cost bias.

Jon M. Kleinberg, Sigal Oren, Manish Raghavan, Nadav Sklar

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness.

Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K. Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

How Do Classifiers Induce Agents to Invest Effort Strategically?

Jon M. Kleinberg, Manish Raghavan

ACM Trans. Economics and Comput., 2020

Algorithmic classification and strategic effort.

Jon M. Kleinberg, Manish Raghavan

SIGecom Exch., 2020

Mitigating bias in algorithmic hiring: evaluating claims and practices.

Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy

Proceedings of the FAT* '20: Conference on Fairness, 2020

The hidden assumptions behind counterfactual explanations and principal reasons.

Solon Barocas, Andrew D. Selbst, Manish Raghavan

Proceedings of the FAT* '20: Conference on Fairness, 2020

Roles for computing in social change.

Rediet Abebe, Solon Barocas, Jon M. Kleinberg, Karen Levy, Manish Raghavan, David G. Robinson

Proceedings of the FAT* '20: Conference on Fairness, 2020

Designing Evaluation Rules That Are Robust to Strategic Behavior.

Jon M. Kleinberg, Manish Raghavan

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

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

Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy

CoRR, 2019

Hiring Under Uncertainty.

Manish Purohit, Sreenivas Gollapudi, Manish Raghavan

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Mapping the Invocation Structure of Online Political Interaction.

Manish Raghavan, Ashton Anderson, Jon M. Kleinberg

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Selection Problems in the Presence of Implicit Bias.

Jon M. Kleinberg, Manish Raghavan

Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

The Externalities of Exploration and How Data Diversity Helps Exploitation.

Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu

Proceedings of the Conference On Learning Theory, 2018

2017

Planning with Multiple Biases.

Jon M. Kleinberg, Sigal Oren, Manish Raghavan

Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

On Fairness and Calibration.

Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger

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.

Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016

Planning Problems for Sophisticated Agents with Present Bias.

Jon M. Kleinberg, Sigal Oren, Manish Raghavan

Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

2014

Deduplicating a places database.

Nilesh N. Dalvi, Marian Olteanu, Manish Raghavan, Philip Bohannon

Proceedings of the 23rd International World Wide Web Conference, 2014