34 citations · 113 across the 36 of their papers we have counts for
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cs.ET2018★ 11 cited
Efficient ConvNets for Analog Arrays
Malte J. Rasch, Tayfun Gokmen, Mattia Rigotti +1
Analog arrays are a promising upcoming hardware technology with the potential to drastically speed up deep learning. Their main advantage is that they compute matrix-vector product…
stat.ML2018★ 34 cited
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel +8
Despite significant recent advances in deep neural networks, training them remains a challenge due to the highly non-convex nature of the objective function. State-of-the-art metho…