Exploring Measuring Distribution Drift Via Multicalibration
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- Over time, our AI predictions degrade. Full Stop. Whether it's concept
- Charlotte Peale (Stanford) https://simons.berkeley.edu/talks/emily-black-stanford-2023-04-26 Multigroup Fairness and the Validity ...
- In this edition of production ML papers to know, we talk with Saurabh Garg from CMU about an approach to model monitoring ...
- A talk at the Wharton statistics seminar about our paper here: https://arxiv.org/abs/2008.08037.
- Authors: Zhun Deng, Cynthia Dwork (Harvard University); Linjun Zhang (Rutgers University) ITCS - Innovations in Theoretical ...
In-Depth Information on Measuring Distribution Drift Via Multicalibration
Udi Wieder (VMware) https://simons.berkeley.edu/talks/udi-wieder-vmware-2023-04-25 Multigroup Fairness and the Validity of ... Omer Reingold (Stanford University) https://simons.berkeley.edu/talks/tbd-396 Algorithmic Aspects of Causal Inference A key ... Michael Kim (UC Berkeley) https://simons.berkeley.edu/talks/michael-kim-uc-berkeley-2023-04-24 Multigroup Fairness and the ... Foundations of Responsible Computing (FORC 2021) Title: Moment
Georgy Noarov (University of Pennsylvania) https://simons.berkeley.edu/talks/georgy-noarov-university-pennsylvania-2023-04-26 ...
That wraps up our extensive overview of Measuring Distribution Drift Via Multicalibration.
