Is Your Model Predicting the Past?

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=0U1GcTDU_ls


Duration: 33:40
744 views
21

Moritz Hardt (UC Berkeley)
https://simons.berkeley.edu/talks/moritz-hardt-uc-berkeley-2023-04-26
Multigroup Fairness and the Validity of Statistical Judgment



Other Videos By Simons Institute for the Theory of Computing


2023-04-29Measuring Our Chances: Risk Prediction in this World and its Betters
2023-04-29Omnipredictors for Constrained Optimization
2023-04-28Who is Fairer: Humans vs. Machines?
2023-04-28Algorithmic Collective Action in Machine Learning
2023-04-28Sample Complexity Bounds for Realizable Multicalibration
2023-04-28Indistinguishable Generative Models of Huge Objects
2023-04-28Complexity-theoretic Implications of Multicalibration: ...
2023-04-27From Pseudorandomness to Multi-Group Fairness and Back
2023-04-27What Statistics Can We Multicalibrate? A Characterization via Property Elicitation
2023-04-27Robust Conditional Average Treatment Effect Estimation via Multi-Accurate Learning
2023-04-27Is Your Model Predicting the Past?
2023-04-27Difficult Lessons on Social Prediction from Wisconsin Public Schools
2023-04-26Unfairness Across the Machine Learning Pipeline
2023-04-26A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning
2023-04-26Algorithms for Multi-Group Learning
2023-04-26Loss Minimization Yields Multicalibration for Large Neural Networks
2023-04-26Measuring Distribution Drift via Multicalibration
2023-04-26Phase Transition in Random Circuit Sampling | Quantum Colloquium
2023-04-26Online Omniprediction
2023-04-26Robust Multivalid Conformal Prediction
2023-04-25Calibration: Unbiased Answers to Arbitrary Questions


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Multigroup Fairness and the Validity of Statistical Judgment
Moritz Hardt