Nikhil Garg

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 27

Top Topics

Convertible Bonds

Distributional Assumptions

Top Venues

Publications

Zhi Liu, Sarah Rankin, Nikhil Garg
Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling. AAAI (2024)
Gabriel Agostini, Emma Pierson, Nikhil Garg
A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing. AAAI (2024)
Zhi Liu, Uma Bhandaram, Nikhil Garg
Quantifying spatial under-reporting disparities in resident crowdsourcing. Nat. Comput. Sci. 4 (1) (2024)
Rajiv Movva, Sidhika Balachandar, Kenny Peng, Gabriel Agostini, Nikhil Garg, Emma Pierson
Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers. NAACL-HLT (2024)
Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg
Reconciling the Accuracy-Diversity Trade-off in Recommendations. WWW (2024)
Sidhika Balachandar, Nikhil Garg, Emma Pierson
Domain constraints improve risk prediction when outcome data is missing. ICLR (2024)
Kenny Peng, Nikhil Garg
Wisdom and Foolishness of Noisy Matching Markets. CoRR (2024)
Kenny Peng, Nikhil Garg
Monoculture in Matching Markets. CoRR (2023)
Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg
Reconciling the accuracy-diversity trade-off in recommendations. CoRR (2023)
Rajiv Movva, Sidhika Balachandar, Kenny Peng, Gabriel Agostini, Nikhil Garg, Emma Pierson
Large language models shape and are shaped by society: A survey of arXiv publication patterns. CoRR (2023)
Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson
Coarse race data conceals disparities in clinical risk score performance. CoRR (2023)
Sidhika Balachandar, Nikhil Garg, Emma Pierson
Domain constraints improve risk prediction when outcome data is missing. CoRR (2023)
Gabriel Agostini, Emma Pierson, Nikhil Garg
A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing. CoRR (2023)
Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov, Nikhil Garg
Interface Design to Mitigate Inflation in Recommender Systems. RecSys (2023)
Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson
Coarse race data conceals disparities in clinical risk score performance. MLHC (2023)
Meena Jagadeesan, Nikhil Garg, Jacob Steinhardt
Supply-Side Equilibria in Recommender Systems. NeurIPS (2023)
Smitha Milli, Emma Pierson, Nikhil Garg
Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems. CoRR (2023)
Zhi Liu, Nikhil Garg
Equity in Resident Crowdsourcing: Measuring Under-reporting without Ground Truth Data. EC (2022)
Lydia T. Liu, Nikhil Garg, Christian Borgs
Strategic ranking. AISTATS (2022)
Meena Jagadeesan, Nikhil Garg, Jacob Steinhardt
Supply-Side Equilibria in Recommender Systems. CoRR (2022)
J. D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, Emma Pierson
Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis. FAccT (2022)
J. D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, Emma Pierson
Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis. CoRR (2022)
Zhi Liu, Nikhil Garg
Equity in Resident Crowdsourcing: Measuring Under-reporting without Ground Truth Data. CoRR (2022)
Gourab K. Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil Garg
Fair ranking: a critical review, challenges, and future directions. FAccT (2022)
Nikhil Garg, Wes Gurnee, David Rothschild, David B. Shmoys
Combatting Gerrymandering with Social Choice: The Design of Multi-member Districts. EC (2022)
Nikhil Garg, Hamid Nazerzadeh
Driver Surge Pricing. Manag. Sci. 68 (5) (2022)
Nikhil Garg, Lodewijk Gelauff, Sukolsak Sakshuwong, Ashish Goel
Who Is in Your Top Three? Optimizing Learning in Elections with Many Candidates. HCOMP (2019)