19 citations · 50 across the 10 of their papers we have counts for
3 papers · 1 filter
Spectral Top-Down Recovery of Latent Tree Models
Yariv Aizenbud, Ariel Jaffe, Meng Wang +5
Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying…
Approximation of Functions over Manifolds: A Moving Least-Squares Approach
Barak Sober, Yariv Aizenbud, David Levin
We present an algorithm for approximating a function defined over a -dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise.…
PCA-Based Out-of-Sample Extension for Dimensionality Reduction
Yariv Aizenbud, Amit Bermanis, Amir Averbuch
Dimensionality reduction methods are very common in the field of high dimensional data analysis. Typically, algorithms for dimensionality reduction are computationally expensive. T…