Abstract: Dimensionality reduction using Variational Autoencoder (VAE) is widely employed in learning diverse state representations, such as in autonomous driving tasks. Conventional VAE-based ...

Abstract: To address the challenge of clustering high-dimensional data, subspace clustering methods, such as Reduced K-means (RKM) have been proposed. These methods identify clusters by simultaneously ...

EPFL researchers have developed new software—now spun-off into a start-up—that eliminates the need for data to be sent to third-party cloud services when AI is used to complete a task. This could ...

Data centers create new jobs, use significantly less water than the clothing and beef industries, and don't drive up electricity rates. Data centers have become an essential part of powering our daily ...

Hyperspectral imaging (HSI) captures rich spectral data across hundreds of contiguous bands for diverse applications. Dimension reduction (DR) techniques are commonly used to map the first three ...