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Why Inverse Problems are Hard
The intersection of Ill-posed, ill-conditioned, and algorithmic constraints
Dec 17, 2024
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Howard Heaton
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Why Inverse Problems are Hard
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Douglas Rachford Splitting
Minimize a sum of nonsmooth functions
Dec 10, 2024
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Howard Heaton
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Douglas Rachford Splitting
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Conditional Gradient / Frank-Wolfe
Revisiting a projection-free method
Dec 3, 2024
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Howard Heaton
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Conditional Gradient / Frank-Wolfe
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November 2024
#1 — Stanley Osher
Partial Differential Equations and Optimization
Nov 25, 2024
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Howard Heaton
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30:27
Proximal Step Illustrated
The lesser-known sibling to gradient step
Nov 24, 2024
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Howard Heaton
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Proximal Step Illustrated
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Welcome to Numerical Optimization
Podcast Trailer
Nov 15, 2024
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Howard Heaton
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1:00
End-to-End Learning with an Optimization Model
Learn the "right problem" for modeling a task
Nov 12, 2024
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Howard Heaton
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End-to-End Learning with an Optimization Model
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Distance to Set is Continuous
An ε-δ argument for uniform continuity
Nov 12, 2024
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Howard Heaton
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Distance to Set is Continuous
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October 2024
Inexact Models and Solution Accuracy
A "worse" model can yield "better" solutions
Oct 19, 2024
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Howard Heaton
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Inexact Models and Solution Accuracy
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Proving Two Sets are Equal
How to make a subset argument
Oct 16, 2024
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Howard Heaton
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Proving Two Sets are Equal
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Limits at Infinity
Refresher on how to formalize limit arguments
Oct 9, 2024
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Howard Heaton
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Limits at Infinity
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Ill-Conditioning in Optimization
3 Ways Something can be "Well-Behaved"
Oct 8, 2024
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Howard Heaton
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Ill-Conditioning in Optimization
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