activity
20182020
most citedNorm matters: efficient and accurate normalization schemes in deep networks

100 citations · 241 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ML2020★ 16 cited

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…

cs.LG2020

Kernel and Rich Regimes in Overparametrized Models

Blake Woodworth, Suriya Gunasekar, Jason D. Lee +5

A recent line of work studies overparametrized neural networks in the "kernel regime," i.e. when the network behaves during training as a kernelized linear predictor, and thus trai…

cs.LG2019★ 56 cited

Kernel and Rich Regimes in Overparametrized Models

Blake Woodworth, Suriya Gunasekar, Pedro Savarese +5

A recent line of work studies overparametrized neural networks in the "kernel regime," i.e. when the network behaves during training as a kernelized linear predictor, and thus trai…

stat.ML2018★ 69 cited

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…

stat.ML2018★ 100 cited

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…