Explaining one of the most emerging methods in machine learning right now
Would you believe me if I were to say that there is a single solution to such different problems as brain decoding in neuroscience, shape reconstruction in computer graphics, color transfer in computer vision, and automatic translation in neural language processing? And if I were to add transfer learning, image registration, and spectral unmixing for musical data to this list and the fact that the solution I am talking about has nothing to do with deep learning? Well, if you couldn’t guess the right answer, then keep on reading as this article is about Optimal Transport (OT): a mathematical theory…
Using game theory to understand the price of selfishness in times of pandemic and climate change
Have you ever wondered why we need all these international organizations that try to make all 195 countries of the world work together towards a common goal? You’ve probably heard from other people (or even presidents of certain countries) that it is just a waste of time and money, right?! Wouldn’t it be much easier if we just let everybody clean their mess?! Surprisingly, the consequences of opting for such an approach can be catastrophic on a global scale, and game theory provides us with a clear explanation of why this is the case.
Social optimum and selfish behavior
To understand the consequences of selfish…
From reading a paper for the first time to writing its complete review in a single Medium article
Peer-reviewing is the cornerstone of modern science, and almost all major conferences in machine learning (ML), such as NeurIPS and ICML, rely on it to decide on whether submitted papers are relevant to the community and original enough to be published there. Unfortunately, with the exponentially increasing number of submitted articles over the last ten years, the reviewing quality has been dropping just as fast, with one-line reviews became widespread. …
Color transfer, Image editing and Automatic translation
As a follow-up of my previous introductory article on optimal transport and a first part of this guide provided by Aurelie Boisbunon here, I will present below how you can solve different tasks with Optimal Transport (OT) in practice using the Python Optimal Transport (POT) toolbox.
To start with, let us install POT using pip from the terminal by simply running
pip3 install otAnd voilà! If everything went well, you now have POT installed and ready to use on your computer. Let me now explain how you can reproduce the results from my previous article.
Color transfer
30,000kms on the thumb around the globe in 1000 words
In the last 8 years of my life, I hitchhiked in almost 30 different countries with a total of around 30,000kms traveled. While I do not hitchhike that much nowadays, I feel that the experiences gained on the road learned me a lot about life and people’s behavior in general, and sharing the lessons I have learned from them with you is what I would like to do below.
Lesson #1: Create your chances
Getting lucky is a matter of you doing something for it to happen.
I learned this one from all the times when I got dropped off in places from which it…
An (almost) math-free guide to understanding the theory behind transfer learning and domain adaptation.
During the NIPS tutorial talk given in 2016, Andrew Ng said that transfer learning — a subarea of machine learning where the model is learned and then deployed in related, yet different, areas — will be the next driver of machine learning commercial success in the years to come. This statement would be hard to contest as avoiding learning large-scale models from scratch would significantly reduce the high computational and annotation efforts required for it and save data science practitioners lots of time, energy, and, ultimately, money.
As an illustration of these latter words, consider Facebook’s DeepFace algorithm that was…
