## GMRES: or how to do fast linear algebra

Linear least-squares system pop up everywhere, and there are many fast way to solve them. We’ll be looking at one such way: GMRES.

I am a math PhD student at the University of Geneva, doing research in tensor networks, numerical linear algebra and machine learning. I like to do data science as a hobby, and I will use this website as a blog and post some of my projects.

Feel free to contact me if you’re interested in any of the things I do!

Linear least-squares system pop up everywhere, and there are many fast way to solve them. We’ll be looking at one such way: GMRES.

We recently made a paper about supervised machine learning using tensors, here’s the gist of how this works.

A lot of data is naturally of ‘low rank’. I will explain what this means, and how to exploit this fact.

Parsing and editing Word documents automatically can be extremely useful, but doing it in Python is not that straightforward.

Finally, let’s look at how we can automatically sharpen images, without knowing how they were blurred in the first place.

Deconvolving and sharpening images is actually pretty tricky. Let’s have a look at some more advanced methods for deconvolution.

In order to automatically sharpen images, we need to first understand how a computer can judge how ‘natural’ an image looks.

Deconvolution is one of the cornerstones of image processing. Let’s take a look at how it works.

I have 15 years worth of email traffic data, let’s take a closer look and discover some fascinating patterns.

2020 was a great year for music, I will look back and give some thoughts on the best albums that came out in 20202.

We use exams to determine how much a student knows, but exams aren’t perfect. How can we estimate the uncertainty in students’ exams scores?

Cross validation is extremely important, but how should we choose the size of our validation and test sets?

I use last.fm to track my music listening. Let’s look at my data to discover how my musical preferences evolve over time.

Normally distributed data is great, but how do you know whether your data is normally distributed?

Judging in figure skating is biased. Let’s use data science to figure out just how bad the issue is.

My first post in this blog