210 citations · 984 across the 29 of their papers we have counts for
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cs.LG2021★ 4 cited
Continuous vs. Discrete Optimization of Deep Neural Networks
Omer Elkabetz, Nadav Cohen
Existing analyses of optimization in deep learning are either continuous, focusing on (variants of) gradient flow, or discrete, directly treating (variants of) gradient descent. Gr…
cs.LG2021★ 2 cited
Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Recent efforts to unravel the mystery of implicit regularization in deep learning have led to a theoretical focus on matrix factorization -- matrix completion via linear neural net…