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Chirag Nagpal
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2020 – today
- 2024
- [c11]Mercy Nyamewaa Asiedu
, Awa Dieng
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. EAAMO 2024: 10:1-10:24 - [c10]Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alexander Nicholas D'Amour, Sanmi Koyejo, Victor Veitch:
Transforming and Combining Rewards for Aligning Large Language Models. ICML 2024 - [i20]Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander D'Amour, Jacob Eisenstein, Chirag Nagpal, Ananda Theertha Suresh:
Theoretical guarantees on the best-of-n alignment policy. CoRR abs/2401.01879 (2024) - [i19]Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alex D'Amour, Sanmi Koyejo, Victor Veitch:
Transforming and Combining Rewards for Aligning Large Language Models. CoRR abs/2402.00742 (2024) - [i18]Kristian Lum, Jacy Reese Anthis, Chirag Nagpal, Alexander D'Amour:
Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation. CoRR abs/2402.12649 (2024) - [i17]Mercy Nyamewaa Asiedu, Awa Dieng, Iskandar Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine A. Heller:
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. CoRR abs/2403.03357 (2024) - [i16]Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Nyamewaa Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah Dewitt, Philip Andrew Mansfield, Sushant Prakash, Katherine A. Heller, Alan Karthikesalingam, Christopher Semturs, Joelle K. Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal:
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. CoRR abs/2403.12025 (2024) - [i15]Adam Fisch, Jacob Eisenstein, Vicky Zayats, Alekh Agarwal, Ahmad Beirami, Chirag Nagpal, Petet Shaw, Jonathan Berant:
Robust Preference Optimization through Reward Model Distillation. CoRR abs/2405.19316 (2024) - [i14]Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar:
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. CoRR abs/2410.08146 (2024) - 2023
- [c9]Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun:
Participatory Personalization in Classification. NeurIPS 2023 - [i13]Hailey James, Chirag Nagpal, Katherine A. Heller, Berk Ustun:
Participatory Systems for Personalized Prediction. CoRR abs/2302.03874 (2023) - [i12]Chirag Nagpal, Vedant Sanil
Recovering Sparse and Interpretable Subgroups with Heterogeneous Treatment Effects with Censored Time-to-Event Outcomes. CoRR abs/2302.12504 (2023) - [i11]Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal, Ahmad Beirami, Alex D'Amour, Dj Dvijotham, Adam Fisch, Katherine A. Heller, Stephen Pfohl, Deepak Ramachandran, Peter Shaw, Jonathan Berant:
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. CoRR abs/2312.09244 (2023) - 2022
- [c8]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. KDD 2022: 3634-3644 - [c7]Chirag Nagpal, Willa Potosnak, Artur Dubrawski:
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data. MLHC 2022: 585-608 - [i10]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. CoRR abs/2202.11089 (2022) - [i9]Chirag Nagpal, Willa Potosnak, Artur Dubrawski:
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data. CoRR abs/2204.07276 (2022) - 2021
- [j1]Chirag Nagpal
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data With Competing Risks. IEEE J. Biomed. Health Informatics 25(8): 3163-3175 (2021) - [c6]Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller:
Deep Cox Mixtures for Survival Regression. MLHC 2021: 674-708 - [c5]Chirag Nagpal, Vincent Jeanselme, Artur Dubrawski:
Deep Parametric Time-to-Event Regression with Time-Varying Covariates. SPACA 2021: 184-193 - [i8]Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller:
Deep Cox Mixtures for Survival Regression. CoRR abs/2101.06536 (2021) - 2020
- [c4]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL 2020: 19-29 - [i7]Chirag Nagpal, Xinyu Li, Artur Dubrawski:
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks. CoRR abs/2003.01176 (2020) - [i6]Chirag Nagpal, Robert E. Tillman, Prashant P. Reddy, Manuela Veloso:
Latent Bayesian Inference for Robust Earnings Estimates. CoRR abs/2004.06565 (2020)
2010 – 2019
- 2019
- [c3]Chirag Nagpal, Xinyu Li, Michael R. Pinsky, Artur Dubrawski:
Dynamically Personalized Detection of Hemorrhage. MLHC 2019: 109-123 - [i5]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR abs/1905.03297 (2019) - [i4]Chirag Nagpal, Rohan Sangave, Amit Chahar, Parth Shah, Artur Dubrawski, Bhiksha Raj:
Nonlinear Semi-Parametric Models for Survival Analysis. CoRR abs/1905.05865 (2019) - 2017
- [c2]Chirag Nagpal, Kyle Miller, Benedikt Boecking, Artur Dubrawski:
An Entity Resolution Approach to Isolate Instances of Human Trafficking Online. NUT@EMNLP 2017: 77-84 - [c1]Chirag Nagpal, Kyle Miller, Tiffany Pellathy, Marilyn Hravnak, Gilles Clermont, Michael R. Pinsky, Artur Dubrawski:
Semi-Supervised Prediction of Comorbid Rare Conditions Using Medical Claims Data. ICDM Workshops 2017: 478-485 - [i3]Abhilasha Ravichander, Shruti Rijhwani, Rajat Kulshreshtha, Chirag Nagpal, Tadas Baltrusaitis, Louis-Philippe Morency:
Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models. CoRR abs/1706.07867 (2017) - 2015
- [i2]Chirag Nagpal, Kyle Miller, Benedikt Boecking, Artur Dubrawski:
An Entity Resolution approach to isolate instances of Human Trafficking online. CoRR abs/1509.06659 (2015) - 2014
- [i1]Chirag Nagpal, Khushboo Singhal:
Twitter User Classification using Ambient Metadata. CoRR abs/1407.8499 (2014)
Coauthor Index
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last updated on 2024-11-19 21:47 CET by the dblp team
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