996 citations · 1.6k across the 32 of their papers we have counts for
Showing 2017Show all
3 papers · 1 filter
cs.AI2017★ 996 cited
Mixed Precision Training
Paulius Micikevicius, Sharan Narang, Jonah Alben +8
Deep neural networks have enabled progress in a wide variety of applications. Growing the size of the neural network typically results in improved accuracy. As model sizes grow, th…
stat.ML2017★ 61 cited
Training Deep AutoEncoders for Collaborative Filtering
Oleksii Kuchaiev, Boris Ginsburg
This paper proposes a novel model for the rating prediction task in recommender systems which significantly outperforms previous state-of-the art models on a time-split Netflix dat…
cs.CL2017★ 99 cited
Factorization tricks for LSTM networks
Oleksii Kuchaiev, Boris Ginsburg
We present two simple ways of reducing the number of parameters and accelerating the training of large Long Short-Term Memory (LSTM) networks: the first one is "matrix factorizatio…