Ravid Shwartz-Ziv | DeepAI

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∙ 06/23/2023

Variance-Covariance Regularization Improves Representation Learning

Transfer learning has emerged as a key approach in the machine learning ...

0 Jiachen Zhu, et al. ∙

∙ 05/24/2023

Reverse Engineering Self-Supervised Learning

Self-supervised learning (SSL) is a powerful tool in machine learning, b...

8 Ido Ben-Shaul, et al. ∙

∙ 04/19/2023

To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review

Deep neural networks have demonstrated remarkable performance in supervi...

0 Ravid Shwartz-Ziv, et al. ∙

∙ 03/01/2023

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization

In this paper, we provide an information-theoretic perspective on Varian...

0 Ravid Shwartz-Ziv, et al. ∙

∙ 10/12/2022

How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization

Despite the clear performance benefits of data augmentations, little is ...

0 Jonas Geiping, et al. ∙

∙ 07/20/2022

What Do We Maximize in Self-Supervised Learning?

In this paper, we examine self-supervised learning methods, particularly...

175 Ravid Shwartz-Ziv, et al. ∙

∙ 05/20/2022

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

Deep learning is increasingly moving towards a transfer learning paradig...

17 Ravid Shwartz-Ziv, et al. ∙

∙ 02/10/2022

Information Flow in Deep Neural Networks

Although deep neural networks have been immensely successful, there is n...

0 Ravid Shwartz-Ziv, et al. ∙

∙ 06/06/2021

Tabular Data: Deep Learning is Not All You Need

A key element of AutoML systems is setting the types of models that will...

0 Ravid Shwartz-Ziv, et al. ∙

∙ 06/08/2020

The Dual Information Bottleneck

The Information Bottleneck (IB) framework is a general characterization ...

0 Zoe Piran, et al. ∙

∙ 11/26/2018

Attentioned Convolutional LSTM InpaintingNetwork for Anomaly Detection in Videos

We propose a semi-supervised model for detecting anomalies in videos ins...

0 Itamar Ben-Ari, et al. ∙

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