ICML 2020. Comprehensive analysis of authors, organizations, and countries.

ICML is one of the most important conferences in Machine Learning and therefore it’s interesting to see who publishes at this conference. So I looked at the accepted papers for ICML 2020 and analyzed authors, organizations, and countries that participated this year. The conference will take place virtually from 13th to 18th July in 2020.

This year there are 1088 accepted papers from 4990 submissions, leading to 21.8% acceptance rate.

Before we dive in, the code can be found at GitHub repo and you can build your own plots in this Colab notebook (no installation required).

Authors

Let’s first take a look at the top authors.

Publishing at ICML is incredibly hard and hence it’s even more impressive to see that so many authors published several papers. Masashi Sugiyama from RIKEN and the university of Tokyo has astonishing 11 accepted papers. He is followed by Michal Valko (DeepMind), Michael Jordan (UC Berkeley), and Dale Schuurmans (Google / U. of Alberta).

Let’s now look at global ranking by the organization. For each organization, I count the set of all papers it participated in. Here are top-30 organizations.

Google dominates the list, participating approximately in 1/10 of the papers published at ICML. It is followed by 3 institutions: MIT, Stanford, and Berkeley. Alphabet’s DeepMind concludes the Top-5 organizations. One note of caution that it’s not fair to say that Google+DeepMind published 114+51 papers as many of these papers were done in collaboration, as we will see next.

Countries

Here is a fun part. I created a mapping between an affiliation of the author and its country, so we can see which countries publish the most.

As a disclaimer, I must warn that creating a mapping for all possible affiliations is a nightmare…