54 citations · 73 across the 7 of their papers we have counts for
7 papers
Reverse Engineering Self-Supervised Learning
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti +2
Self-supervised learning (SSL) is a powerful tool in machine learning, but understanding the learned representations and their underlying mechanisms remains a challenge. This paper…
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions
Ido Ben-Shaul, Tomer Galanti, Shai Dekel
Multiplication layers are a key component in various influential neural network modules, including self-attention and hypernetwork layers. In this paper, we investigate the approxi…
Super-resolution on the Sphere using Convex Optimization
Tamir Bendory, Shai Dekel, Arie Feuer
This paper considers the problem of recovering an ensemble of Diracs on a sphere from its low resolution measurements. The Diracs can be located at any location on the sphere, not…
Unified Convex Optimization Approach to Super-Resolution Based on Localized Kernels
Tamir Bendory, Shai Dekel, Arie Feuer
The problem of resolving the fine details of a signal from its coarse scale measurements or, as it is commonly referred to in the literature, the super-resolution problem arises na…
Exact recovery of Dirac ensembles from the projection onto spaces of spherical harmonics
Tamir Bendory, Shai Dekel, Arie Feuer
In this work we consider the problem of recovering an ensemble of Diracs on the sphere from its projection onto spaces of spherical harmonics. We show that under an appropriate sep…
Hardy spaces associated with non-negative self-adjoint operators
S. Dekel, G. Kerkyacharian, G. Kyriazis +1
Maximal and atomic Hardy spaces Hp and HAp , are considered in the setting of a doubling metric measure space in the presence of a non-negative self-adjoint operator whose heat ker…