no code implementations • 26 Feb 2024 • Kenny Peng, Nikhil Garg
Each student has a true value $v$, but each college $c$ ranks the student according to an independently drawn estimated value $v + X_c$ for $X_c\sim \mathcal{D}.$ We ask a basic question about the resulting stable matching: How noisy is the set of matched students?
no code implementations • 15 Aug 2023 • Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan
Machine learning (ML) methods are proliferating in scientific research.
no code implementations • 27 Jul 2023 • Kenny Peng, Manish Raghavan, Emma Pierson, Jon Kleinberg, Nikhil Garg
In recommendation settings, there is an apparent trade-off between the goals of accuracy (to recommend items a user is most likely to want) and diversity (to recommend items representing a range of categories).
1 code implementation • 20 Jul 2023 • Rajiv Movva, Sidhika Balachandar, Kenny Peng, Gabriel Agostini, Nikhil Garg, Emma Pierson
Large language models (LLMs) are dramatically influencing AI research, spurring discussions on what has changed so far and how to shape the field's future.
no code implementations • 6 Aug 2021 • Kenny Peng, Arunesh Mathur, Arvind Narayanan
Machine learning datasets have elicited concerns about privacy, bias, and unethical applications, leading to the retraction of prominent datasets such as DukeMTMC, MS-Celeb-1M, and Tiny Images.