Manish Raghavan

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 52

Top Topics

Greedy Algorithm

Mechanism Design

Top Venues

Publications

Rohan Alur, Manish Raghavan, Devavrat Shah
Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction. CoRR (2024)
Cynthia Dwork, Kristjan H. Greenewald, Manish Raghavan
Synthetic Census Data Generation via Multidimensional Multiset Sum. CoRR (2024)
Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg
Reconciling the Accuracy-Diversity Trade-off in Recommendations. WWW (2024)
Manish Raghavan
What Should We Do when Our Ideas of Fairness Conflict? Commun. ACM 67 (1) (2024)
Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan
Equilibria, Efficiency, and Inequality in Network Formation for Hiring and Opportunity. CoRR (2024)
Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan
Content Moderation and the Formation of Online Communities: A Theoretical Framework. WWW (2024)
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits. SIAM J. Comput. 52 (2) (2023)
Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung
Auditing for Human Expertise. NeurIPS (2023)
Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung
Auditing for Human Expertise. CoRR (2023)
Chris Hays, Zachary Schutzman, Manish Raghavan, Erin Walk, Philipp Zimmer
Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection. WWW (2023)
Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan
Content Moderation and the Formation of Online Communities: A Theoretical Framework. CoRR (2023)
Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg
Reconciling the accuracy-diversity trade-off in recommendations. CoRR (2023)
Chris Hays, Zachary Schutzman, Manish Raghavan, Erin Walk, Philipp Zimmer
Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection. CoRR (2023)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. CoRR (2022)
Sarah H. Cen, Manish Raghavan
The Right to be an Exception to a Data-Driven Rule. CoRR (2022)
Emily Black, Manish Raghavan, Solon Barocas
Model Multiplicity: Opportunities, Concerns, and Solutions. FAccT (2022)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. EC (2022)
Jon M. Kleinberg, Manish Raghavan
Algorithmic monoculture and social welfare. Proc. Natl. Acad. Sci. USA 118 (22) (2021)
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
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems. CoRR (2021)
Jon M. Kleinberg, Manish Raghavan
Algorithmic Monoculture and Social Welfare. CoRR (2021)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan, Nadav Sklar
Stochastic model for sunk cost bias. UAI (2021)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan, Nadav Sklar
Stochastic Model for Sunk Cost Bias. CoRR (2021)
Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K. Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness. FAccT (2021)
Jon M. Kleinberg, Manish Raghavan
Designing Evaluation Rules That Are Robust to Strategic Behavior. AAAI (2020)
Rediet Abebe, Solon Barocas, Jon M. Kleinberg, Karen Levy, Manish Raghavan, David G. Robinson
Roles for computing in social change. FAT* (2020)
Jon M. Kleinberg, Manish Raghavan
How Do Classifiers Induce Agents to Invest Effort Strategically? ACM Trans. Economics and Comput. 8 (4) (2020)
Solon Barocas, Andrew D. Selbst, Manish Raghavan
The hidden assumptions behind counterfactual explanations and principal reasons. FAT* (2020)
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
Greedy Algorithm almost Dominates in Smoothed Contextual Bandits. CoRR (2020)
Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K. Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness. CoRR (2020)
Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy
Mitigating bias in algorithmic hiring: evaluating claims and practices. FAT* (2020)
Jon M. Kleinberg, Manish Raghavan
Algorithmic classification and strategic effort. SIGecom Exch. 18 (2) (2020)
Manish Purohit, Sreenivas Gollapudi, Manish Raghavan
Hiring Under Uncertainty. ICML (2019)
Jon M. Kleinberg, Manish Raghavan
How Do Classifiers Induce Agents to Invest Effort Strategically? EC (2019)
Solon Barocas, Andrew D. Selbst, Manish Raghavan
The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons. CoRR (2019)
Rediet Abebe, Solon Barocas, Jon M. Kleinberg, Karen Levy, Manish Raghavan, David G. Robinson
Roles for Computing in Social Change. CoRR (2019)
Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy
Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices. CoRR (2019)
Manish Raghavan, Manish Purohit, Sreenivas Gollapudi
Hiring Under Uncertainty. CoRR (2019)
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
The Externalities of Exploration and How Data Diversity Helps Exploitation. CoRR (2018)
Jon M. Kleinberg, Manish Raghavan
How Do Classifiers Induce Agents To Invest Effort Strategically? CoRR (2018)
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
The Externalities of Exploration and How Data Diversity Helps Exploitation. COLT (2018)
Manish Raghavan, Ashton Anderson, Jon M. Kleinberg
Mapping the Invocation Structure of Online Political Interaction. WWW (2018)
Manish Raghavan, Ashton Anderson, Jon M. Kleinberg
Mapping the Invocation Structure of Online Political Interaction. CoRR (2018)
Jon M. Kleinberg, Manish Raghavan
Selection Problems in the Presence of Implicit Bias. CoRR (2018)
Jon M. Kleinberg, Manish Raghavan
Selection Problems in the Presence of Implicit Bias. ITCS (2018)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan
Planning with Multiple Biases. EC (2017)
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger
On Fairness and Calibration. CoRR (2017)
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger
On Fairness and Calibration. NIPS (2017)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
Inherent Trade-Offs in the Fair Determination of Risk Scores. ITCS (2017)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan
Planning with Multiple Biases. CoRR (2017)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
Inherent Trade-Offs in the Fair Determination of Risk Scores. CoRR (2016)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan
Planning Problems for Sophisticated Agents with Present Bias. EC (2016)
Jon M. Kleinberg, Sigal Oren, Manish Raghavan
Planning Problems for Sophisticated Agents with Present Bias. CoRR (2016)
Nilesh N. Dalvi, Marian Olteanu, Manish Raghavan, Philip Bohannon
Deduplicating a places database. WWW (2014)