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title
Spaghetti Optimization
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Two years ago, I started to study Computational Optimal Transport (OT), and, now, it is time to wrap up informally the main ideas by using an …
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site name
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Stefano Gualandi
updated
2026-03-09 00:11:35
raw text
Spaghetti Optimization Spaghetti Optimization My cookbook about Math, Algorithms, and Programming RSS Blog Archives Credits An Informal and Biased Tutorial on Kantorovich-Wasserstein Distances Dec 31 st , 2018 | Comments Two years ago, I started to study Computational Optimal Transport (OT) , and, now, it is time to wrap up informally the main ideas by using an Operations Research (OR) perspective with a Machine Learning (ML) motivation. Yes, an OR perspective. Why an OR perspective? Well, because most of the current theoretical works on Optimal Transport have a strong functional analysis bias, and, hence, the are pretty far to be an “easy reading” for anyone working on a different research area. Since I’m more comfortable with “summations” than with “integrations”, in this post I focus only on Discrete Optimal Transport and on Kantorovich-Wasserstein distances between a pair of discrete measures. Why an ML motivation? Because measuring ...
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