3 citations · 4 across the 16 of their papers we have counts for
17 papers
A Geometric Analysis of Initialization Bias in Spherical -means in the Weak Signal Regime
Amnon Balanov, Tamir Bendory
We study initialization bias in spherical -means for weakly informative directional mixtures. We model the observations by a -component von Mises-Fisher mixture with a small…
The generalized method of moments is (almost) statistically efficient in low-SNR Gaussian latent-variable models
Amnon Balanov, Tamir Bendory, Dan Edidin
We study estimation in the low signal-to-noise ratio (SNR) regime for a broad class of Gaussian latent-variable models, including Gaussian mixtures and orbit recovery problems. We…
Projected multi-reference alignment
Amnon Balanov, Josh Katz, Tamir Bendory +1
Motivated by structural biology applications, we study the projected multi-reference alignment (MRA) model, in which an unknown signal is observed through noisy samples, each gener…
The interplay of signal-to-noise ratio and variance misspecification in Gaussian mixtures
Vladimir Serov, Amnon Balanov, Tamir Bendory
We study estimation and clustering in Gaussian mixture models under variance misspecification. Observations are generated with true variance , while the component means are es…
Group-invariant moments under tomographic projections
Amnon Balanov, Tamir Bendory, Dan Edidin
Let be an unknown object, and suppose the observations are tomographic projections of randomly rotated copies of of the form , wh…
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…