(ISEA) International Sports Engineering Association’s Post

Don't miss our lecture on Friday!

Join us for the next edition of our online lecture series on Sports Engineering, kazuya Seo from Kogakuin University will present the concept of designing the equipment on the basis of sparse modelling. Athletes' performance depends on both the athlete and the equipment, and both must work in harmony. Generally, there are many design variables during the design stage. It is also difficult to estimate the index of performances multiple times due to time and budget constraints. This brings us to sparse modelling. The number of estimations of the index of performance is few, but design variables are many. Sparse modelling is a technique in machine learning that aims to represent data using a minimal set of features, emphasising simplicity and interpretability.

This content isn’t available here

Access this content and more in the LinkedIn app

To view or add a comment, sign in

Explore topics