50 citations · 50 across the 2 of their papers we have counts for
5 papers · 1 filter
Task Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates
Chen Zeno, Itay Golan, Elad Hoffer +1
Background: Catastrophic forgetting is the notorious vulnerability of neural networks to the changes in the data distribution during learning. This phenomenon has long been conside…
Task Agnostic Continual Learning Using Online Variational Bayes
Chen Zeno, Itay Golan, Elad Hoffer +1
Catastrophic forgetting is the notorious vulnerability of neural networks to the change of the data distribution while learning. This phenomenon has long been considered a major ob…
Norm matters: efficient and accurate normalization schemes in deep networks
Elad Hoffer, Ron Banner, Itay Golan +1
Over the past few years, Batch-Normalization has been commonly used in deep networks, allowing faster training and high performance for a wide variety of applications. However, the…
On the Blindspots of Convolutional Networks
Elad Hoffer, Shai Fine, Daniel Soudry
Deep convolutional network has been the state-of-the-art approach for a wide variety of tasks over the last few years. Its successes have, in many cases, turned it into the default…
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer, Itay Hubara, Daniel Soudry
Background: Deep learning models are typically trained using stochastic gradient descent or one of its variants. These methods update the weights using their gradient, estimated fr…