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Multicalibration, Universal Adaptability and Causality
Simons Institute for the Theory of Computing
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1:02:41
Multicalibration and Outcome Indistinguishability I
Simons Institute for the Theory of Computing
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32:46
Measuring Distribution Drift via Multicalibration
Simons Institute for the Theory of Computing
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1:21:05
Multicalibration: Towards Fair Decision Making
Simons Institute for the Theory of Computing
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48:11
Online Adversarial Multicalibration And (Multi)Calibeating
Simons Institute for the Theory of Computing
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39:30
Double Machine Learning for Causal and Treatment Effects
Becker Friedman Institute University of Chicago
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1:26:41
Closing the Discovery Loop with Low-Dimensional Models and Causal Perturbations with Tatiana Engel
Kempner Institute at Harvard University
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31:39
A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning
Simons Institute for the Theory of Computing
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19:40
Moment Multicalibration for Uncertainty Estimation
FORC Foundations of Responsible Computing
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30:45
What Statistics Can We Multicalibrate? A Characterization via Property Elicitation
Simons Institute for the Theory of Computing
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4:51
11.6 - Parametric Interventions for Causal Discovery
Brady Neal - Causal Inference
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