1.1k citations · 7.8k across the 180 of their papers we have counts for
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stat.ML2015★ 6 cited
A Scale Mixture Perspective of Multiplicative Noise in Neural Networks
Eric Nalisnick, Anima Anandkumar, Padhraic Smyth
Corrupting the input and hidden layers of deep neural networks (DNNs) with multiplicative noise, often drawn from the Bernoulli distribution (or 'dropout'), provides regularization…
stat.ML2015★ 62 cited
Fast and Guaranteed Tensor Decomposition via Sketching
Yining Wang, Hsiao-Yu Tung, Alexander Smola +1
Tensor CANDECOMP/PARAFAC (CP) decomposition has wide applications in statistical learning of latent variable models and in data mining. In this paper, we propose fast and randomize…