Sendhil Mullainathan

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 36

Top Topics

Substantially Higher

Probabilistic Model

Language Generation

Top Venues

Publications

Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function. CoRR (2024)
Jon M. Kleinberg, Sendhil Mullainathan
Language Generation in the Limit. CoRR (2024)
Keyon Vafa, Justin Y. Chen, Jon M. Kleinberg, Sendhil Mullainathan, Ashesh Rambachan
Evaluating the World Model Implicit in a Generative Model. CoRR (2024)
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
Use large language models to promote equity. CoRR (2023)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. CoRR (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, Sendhil Mullainathan
Simplicity creates inequity: implications for fairness, stereotypes, and interpretability (invited paper). STOC (2021)
Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster
The Data Station: Combining Data, Compute, and Market Forces. CoRR (2020)
Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan
Characterizing the Value of Information in Medical Notes. EMNLP (Findings) (2020)
Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan
Characterizing the Value of Information in Medical Notes. CoRR (2020)
Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein
Algorithms as discrimination detectors. Proc. Natl. Acad. Sci. USA 117 (48) (2020)
Justine Zhang, Sendhil Mullainathan, Cristian Danescu-Niculescu-Mizil
Quantifying the Causal Effects of Conversational Tendencies. Proc. ACM Hum. Comput. Interact. 4 (CSCW2) (2020)
Justine Zhang, Sendhil Mullainathan, Cristian Danescu-Niculescu-Mizil
Quantifying the Causal Effects of Conversational Tendencies. CoRR (2020)
Andrew C. Miller, Ziad Obermeyer, John P. Cunningham, Sendhil Mullainathan
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography. ICML (2019)
Maithra Raghu, Katy Blumer, Greg Corrado, Jon M. Kleinberg, Ziad Obermeyer, Sendhil Mullainathan
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort. CoRR (2019)
Ziad Obermeyer, Sendhil Mullainathan
Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People. FAT (2019)
Drew Fudenberg, Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
Measuring the Completeness of Theories. CoRR (2019)
Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein
Discrimination in the Age of Algorithms. CoRR (2019)
Jon M. Kleinberg, Sendhil Mullainathan
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability. EC (2019)
Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Robert D. Kleinberg, Sendhil Mullainathan, Jon M. Kleinberg
Direct Uncertainty Prediction for Medical Second Opinions. ICML (2019)
Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan, Jon M. Kleinberg
Direct Uncertainty Prediction with Applications to Healthcare. CoRR (2018)
Sendhil Mullainathan
Algorithmic Fairness and the Social Welfare Function. EC (2018)
Jon M. Kleinberg, Sendhil Mullainathan
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability. CoRR (2018)
Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, Sendhil Mullainathan
A Probabilistic Model of Cardiac Physiology and Electrocardiograms. CoRR (2018)
Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan
Measuring the Stability of EHR- and EKG-based Predictive Models. CoRR (2018)
Himabindu Lakkaraju, Jon M. Kleinberg, Jure Leskovec, Jens Ludwig, Sendhil Mullainathan
The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables. KDD (2017)
Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
The Theory is Predictive, but is it Complete? An Application to Human Perception of Randomness. CoRR (2017)
Jon M. Kleinberg, Sendhil Mullainathan, Johan Ugander
Comparison-Based Choices. CoRR (2017)
Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
The Theory is Predictive, but is it Complete?: An Application to Human Perception of Randomness. EC (2017)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
Inherent Trade-Offs in the Fair Determination of Risk Scores. ITCS (2017)
Jon M. Kleinberg, Sendhil Mullainathan, Johan Ugander
Comparison-based Choices. EC (2017)
Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
Assessing Human Error Against a Benchmark of Perfection. ACM Trans. Knowl. Discov. Data 11 (4) (2017)
Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
Assessing Human Error Against a Benchmark of Perfection. KDD (2016)
Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
Inherent Trade-Offs in the Fair Determination of Risk Scores. CoRR (2016)
Dean S. Karlan, Margaret McConnell, Sendhil Mullainathan, Jonathan Zinman
Getting to the Top of Mind: How Reminders Increase Saving. Manag. Sci. 62 (12) (2016)
Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
Assessing Human Error Against a Benchmark of Perfection. CoRR (2016)
Himabindu Lakkaraju, Jure Leskovec, Jon M. Kleinberg, Sendhil Mullainathan
A Bayesian Framework for Modeling Human Evaluations. SDM (2015)
Sendhil Mullainathan
Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning? KDD (2014)
Jon M. Kleinberg, Sendhil Mullainathan
Resource Bounds and Combinations of Consensus Objects. PODC (1993)