STAGE 1. ONLINE

THE ONLINE STAGE HAS STARTED

REGISTRATION IS OVER. THE FINAL COUNT IS 2756 PARTICIPANTS FROM 83 COUNTRIES!

There are two separate tracks during the online stage. From the machine learning perspective, the tracks will be similar, yet the restrictions put on the solutions are different for each track.

The first track will be a traditional data science competition. Having a labeled training data set, participants will be asked to make a prediction for the test data and submit their predictions to the leaderboard. In this track, participants can produce arbitrarily complex models. If you like to use 4-level stacking or deep neural networks, this is the right track for you – you will only need to submit test predictions. However, those who qualify for the finals will be asked to submit the full code of the solution for validation by the judges.

In real world problems, efficiency is as important as quality. Complex and resource-intensive solutions will not fit the strict time and space restrictions often imposed by an application. That is why in the second competition track, your task will be to solve the same problem as was in track one, but with tight restrictions on the time and on the memory . If you like the most efficient solutions, this is the right track for you.

We hope that the two tracks will make the olympiad fascinating for both machine learning competition experts and competitive programming masters, Kaggle winners and ACM champions, as well as everyone eager to solve real world problems with Data. Moreover, we encourage people with different backgrounds, ML and ACM, to team up and push Data Analysis to new frontiers.

This year the online task is coming from astronomy. It is focused on building a model that would predict the position of space objects using simulation data. The task was given by Russian Astronomical Science Center (ASC) and adopted for the Olympiad by the Laboratory of Methods for Big Data Analysis (LAMBDA, HSE University).Predicting the position of satellites is one of the most important tasks in astronomy. For example, information on the exact position of satellites in orbit is necessary to avoid extremely dangerous satellite collisions. Each collision leads not only to satellites destruction, but also results in thousands of space debris pieces. For instance, Iridium-Coscos collision in 2009 increased number of space debris by approximately 13%. Further collisions may result in Kessler syndrome and the inaccessibility of outer space. Also, a more accurate prediction of satellite position will help calculate more eﬃcient maneuvers to save propellant and extend satellite life in orbit.

Online Stage Results