609 citations · 610 across the 2 of their papers we have counts for
5 papers
Revisiting Distributed Synchronous SGD
Xinghao Pan, Jianmin Chen, Rajat Monga +2
Distributed training of deep learning models on large-scale training data is typically conducted with asynchronous stochastic optimization to maximize the rate of updates, at the c…
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi, Ashish Agarwal, Paul Barham +37
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…
Exploring the Limits of Language Modeling
Rafal Jozefowicz, Oriol Vinyals, Mike Schuster +2
In this work we explore recent advances in Recurrent Neural Networks for large scale Language Modeling, a task central to language understanding. We extend current models to deal w…
Fast optimization of Multithreshold Entropy Linear Classifier
Rafal Jozefowicz, Wojciech Marian Czarnecki
Multithreshold Entropy Linear Classifier (MELC) is a density based model which searches for a linear projection maximizing the Cauchy-Schwarz Divergence of dataset kernel density e…
Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation
Wojciech Marian Czarnecki, Rafał Józefowicz, Jacek Tabor
Representation learning is currently a very hot topic in modern machine learning, mostly due to the great success of the deep learning methods. In particular low-dimensional repres…