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Learning from Outcomes - Evidence-Consistent Rankings

Offered By: IEEE via YouTube

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IEEE FOCS: Foundations of Computer Science Courses Data Analysis Courses Fairness Courses

Course Description

Overview

Explore a 21-minute IEEE conference talk on evidence-consistent rankings and learning from outcomes. Delve into the importance of studying rankings, fairness considerations, and misrepresentation issues. Examine the concept of evidence-based perspective, domination compatibility, and evidence consistency. Understand multi-accuracy and its application through a toy example. Analyze self-reference in rankings and engage in a thought-provoking discussion on the implications of these concepts for real-world applications.

Syllabus

Intro
Why study rankings
Learning from outcomes
Theorem
Fairness
Misrepresentation
Evidencebased perspective
Domination Compatibility
Evidence Consistency
Multi Accuracy
Toy Example
SelfReference
Discussion


Taught by

IEEE FOCS: Foundations of Computer Science

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