no code implementations • 1 Oct 2021 • Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger
We first present the Robust AutoEncoder (RAE) objective as a minimization problem for splitting the data into inliers and outliers.
1 code implementation • 11 May 2021 • Yariv Aizenbud, Barak Sober
Assuming that the data was sampled uniformly from a tubular neighborhood of $\mathcal{M}\in \mathcal{C}^k$, a compact manifold without boundary, we present an algorithm that takes a point $r$ from the tubular neighborhood and outputs $\hat p_n\in \mathbb{R}^D$, and $\widehat{T_{\hat p_n}\mathcal{M}}$ an element in the Grassmanian $Gr(d, D)$.
1 code implementation • 26 Feb 2021 • Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger
For large trees, a common approach, termed divide-and-conquer, is to recover the tree structure in two steps.
3 code implementations • 28 Feb 2020 • Ariel Jaffe, Noah Amsel, Yariv Aizenbud, Boaz Nadler, Joseph T. Chang, Yuval Kluger
A common assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model.
no code implementations • 2 Nov 2017 • Barak Sober, Yariv Aizenbud, David Levin
The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold.
no code implementations • 11 Jul 2017 • Yariv Aizenbud, Amir Averbuch, Gil Shabat, Guy Ziv
This paper provides a new similarity detection algorithm.
no code implementations • 5 Sep 2016 • Yariv Aizenbud, Yoel Shkolnisky
In this paper, we attempt to make the first steps towards rigorous mathematical analysis of the heterogeneity problem in cryo-electron microscopy.
no code implementations • 28 Jun 2016 • Moshe Salhov, Ofir Lindenbaum, Yariv Aizenbud, Avi Silberschatz, Yoel Shkolnisky, Amir Averbuch
Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden parameters by utilizing distance metrics that consider the set of attributes as a single monolithic set.
no code implementations • 3 Nov 2015 • Yariv Aizenbud, Amit Bermanis, Amir Averbuch
We prove that the error of the proposed algorithm is bounded.