29 citations · 144 across the 30 of their papers we have counts for
3 papers · 2 filters
A case where a spindly two-layer linear network whips any neural network with a fully connected input layer
Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid
It was conjectured that any neural network of any structure and arbitrary differentiable transfer functions at the nodes cannot learn the following problem sample efficiently when…
Measuring and Harnessing Transference in Multi-Task Learning
Christopher Fifty, Ehsan Amid, Zhe Zhao +3
Multi-task learning can leverage information learned by one task to benefit the training of other tasks. Despite this capacity, naive formulations often degrade performance and in…
Reparameterizing Mirror Descent as Gradient Descent
Ehsan Amid, Manfred K. Warmuth
Most of the recent successful applications of neural networks have been based on training with gradient descent updates. However, for some small networks, other mirror descent upda…