Skip to yearly menu bar Skip to main content


Tutorial

Identifying Structure in Data: All you need to know about Dimensionality Reduction, Clustering and more

Constantin Seibold

[ ] [ Project Page ]
Thu 12 Jun 11 a.m. PDT — 3 p.m. PDT

Abstract:

This tutorial explores techniques for dataset curation, quality monitoring, dimensionality reduction (t-SNE, UMAP, h-NNE), and clustering (k-means, DBSCAN, FINCH). Attendees will learn how to use these methods to understand structure, reduce bias, detect outliers, and improve performance in AI and CV workflows.

Chat is not available.