3 papers
stat.ME2026
On the discretization of the object space in inverse problems with application to cryo-electron microscopy
Gilles Mordant, Luke Evans, David Silva-Sánchez +2
In many inverse problems, the aim is to recover a probability distribution on a latent (or object state) space from indirect, noisy observations. When the observations can be model…
stat.ML2026
The Catastrophic Failure of The k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
Roy R. Lederman, David Silva-Sánchez, Ziling Chen +3
Lloyd's k-means algorithm is one of the most widely used clustering methods. We prove that in high-dimensional, high-noise settings, the algorithm exhibits catastrophic failure: wi…
stat.ML2025
An Observation on Lloyd's k-Means Algorithm in High Dimensions
David Silva-Sánchez, Roy R. Lederman
Clustering and estimating cluster means are core problems in statistics and machine learning, with k-means and Expectation Maximization (EM) being two widely used algorithms. In th…