Sendhil Mullainathan

According to our database, Sendhil Mullainathan authored at least 31 papers between 1993 and 2024.

Collaborative distances:

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

2024

Large Language Models: An Applied Econometric Framework.

Jens Ludwig, Sendhil Mullainathan, Ashesh Rambachan

CoRR, 2024

Evaluating the World Model Implicit in a Generative Model.

Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Language Generation in the Limit.

Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function.

Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Use large language models to promote equity.

Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa

CoRR, 2023

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

2021

Simplicity creates inequity: implications for fairness, stereotypes, and interpretability (invited paper).

Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

2020

Algorithms as discrimination detectors.

Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein

Proc. Natl. Acad. Sci. USA, 2020

Quantifying the Causal Effects of Conversational Tendencies.

Justine Zhang, Sendhil Mullainathan, Cristian Danescu-Niculescu-Mizil

Proc. ACM Hum. Comput. Interact., 2020

The Data Station: Combining Data, Compute, and Market Forces.

Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster

CoRR, 2020

Characterizing the Value of Information in Medical Notes.

Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

Measuring the Completeness of Theories.

Drew Fudenberg, Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan

CoRR, 2019

The Algorithmic Automation Problem: Prediction, Triage, and Human Effort.

Maithra Raghu, Katy Blumer, Greg Corrado, Jon M. Kleinberg, Ziad Obermeyer, Sendhil Mullainathan

CoRR, 2019

Discrimination in the Age of Algorithms.

Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein

CoRR, 2019

Direct Uncertainty Prediction for Medical Second Opinions.

Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Robert D. Kleinberg, Sendhil Mullainathan, Jon M. Kleinberg

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

Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography.

Andrew C. Miller, Ziad Obermeyer, John P. Cunningham, Sendhil Mullainathan

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

Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People.

Ziad Obermeyer, Sendhil Mullainathan

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

Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability.

Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

2018

Measuring the Stability of EHR- and EKG-based Predictive Models.

Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan

CoRR, 2018

A Probabilistic Model of Cardiac Physiology and Electrocardiograms.

Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, Sendhil Mullainathan

CoRR, 2018

Direct Uncertainty Prediction with Applications to Healthcare.

Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan, Jon M. Kleinberg

CoRR, 2018

Algorithmic Fairness and the Social Welfare Function.

Sendhil Mullainathan

Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

2017

Assessing Human Error Against a Benchmark of Perfection.

Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan

ACM Trans. Knowl. Discov. Data, 2017

Comparison-based Choices.

Jon M. Kleinberg, Sendhil Mullainathan, Johan Ugander

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

The Theory is Predictive, but is it Complete?: An Application to Human Perception of Randomness.

Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan

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

The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables.

Himabindu Lakkaraju, Jon M. Kleinberg, Jure Leskovec, Jens Ludwig, Sendhil Mullainathan

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 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

Getting to the Top of Mind: How Reminders Increase Saving.

Dean S. Karlan, Margaret McConnell, Sendhil Mullainathan, Jonathan Zinman

Manag. Sci., 2016

2015

A Bayesian Framework for Modeling Human Evaluations.

Himabindu Lakkaraju, Jure Leskovec, Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

2014

Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning?

Sendhil Mullainathan

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

1993

Resource Bounds and Combinations of Consensus Objects.

Jon M. Kleinberg, Sendhil Mullainathan

Proceedings of the Twelth Annual ACM Symposium on Principles of Distributed Computing, 1993