Practical Info
Speaker : Thibault Debatty (Royal Military Academy
Time : 13h00 – 14h00
Room : P.2NO8.08
Short Abstract
Similarity search is an essential component of machine learning algorithms. However, performing efficient similarity search can be extremely challenging, especially if the dataset is distributed between multiple computers, and even more if the similarity measure is not a metric. With the rise of Big Data processing, these challenging datasets are actually more and more common. In this presentation, we show how k nearest neighbors (k-nn) graphs can be used to perform similarity search, clustering and anomaly detection.