11 citations · 18 across the 7 of their papers we have counts for
8 papers
Artificial Expert Intelligence through PAC-reasoning
Shai Shalev-Shwartz, Amnon Shashua, Gal Beniamini +6
Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with cr…
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…
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks
Tomer Galanti, Liane Galanti, Ido Ben-Shaul
Recent results in the literature suggest that the penultimate (second-to-last) layer representations of neural networks that are trained for classification exhibit a clustering pro…
Nearest Class-Center Simplification through Intermediate Layers
Ido Ben-Shaul, Shai Dekel
Recent advances in theoretical Deep Learning have introduced geometric properties that occur during training, past the Interpolation Threshold -- where the training error reaches z…
Sparsity-Probe: Analysis tool for Deep Learning Models
Ido Ben-Shaul, Shai Dekel
We propose a probe for the analysis of deep learning architectures that is based on machine learning and approximation theoretical principles. Given a deep learning architecture an…
Certainty Pooling for Multiple Instance Learning
Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp +1
Multiple Instance Learning is a form of weakly supervised learning in which the data is arranged in sets of instances called bags with one label assigned per bag. The bag level cla…
Solving the functional Eigen-Problem using Neural Networks
Ido Ben-Shaul, Leah Bar, Nir Sochen
In this work, we explore the ability of NN (Neural Networks) to serve as a tool for finding eigen-pairs of ordinary differential equations. The question we aime to address is wheth…