Understanding Multicalibration Towards Fair Decision Making
Welcome to our comprehensive guide on Multicalibration Towards Fair Decision Making. Michael Kim (UC Berkeley) https://simons.berkeley.edu/talks/tbd-459 Data-Driven
Key Takeaways about Multicalibration Towards Fair Decision Making
- Aaron Roth (University of Pennsylvania) https://simons.berkeley.edu/talks/online-adversarial-
- Authors: Zhun Deng, Cynthia Dwork (Harvard University); Linjun Zhang (Rutgers University) ITCS - Innovations in Theoretical ...
- Gal Yona (Weizmann Institute) https://simons.berkeley.edu/talks/
- Fair
- Guy Rothblum (Weizmann Institute of Science) https://simons.berkeley.edu/talks/multi-group-approach-algorithmic-fairness ...
Detailed Analysis of Multicalibration Towards Fair Decision Making
Michael Kim (UC Berkeley) https://simons.berkeley.edu/talks/michael-kim-uc-berkeley-2023-04-24 Multigroup Fairness and the ... A tutorial covering Omer Reingold (Stanford University) https://simons.berkeley.edu/talks/tbd-396 Algorithmic Aspects of Causal Inference A key ...
Foundations of Responsible Computing (FORC 2021) Title: Moment
In summary, understanding Multicalibration Towards Fair Decision Making gives us a better perspective.
