Large Scale Distributed Deep Networks
Recent work in unsupervised feature learning and deep learning has shown that being able to train large models can dramatically improve performance. In this paper, we consider t...
Publications
4 shownTensorFlow: a system for large-scale machine learning
TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. Tensor-Flow uses dataflow graphs to represent computation, shared state, ...
Building high-level features using large scale unsupervised learning
We consider the problem of building high-level, class-specific feature detectors from only unlabeled data. For example, is it possible to learn a face detector using only unlabe...
Revisiting Distributed Synchronous SGD
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 th...
Frequent Co-Authors
Researcher Info
- h-index
- 4
- Publications
- 4
- Citations
- 10,487
- Institution
- Google (United States)
External Links
Impact Metrics
h-index
4
h-index: Number of publications with at least h citations each.