14.1k citations · 34.6k across the 53 of their papers we have counts for
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Modeling Documents with Deep Boltzmann Machines
Nitish Srivastava, Ruslan R Salakhutdinov, Geoffrey E. Hinton
We introduce a Deep Boltzmann Machine model suitable for modeling and extracting latent semantic representations from a large unstructured collection of documents. We overcome the…
Speech Recognition with Deep Recurrent Neural Networks
Alex Graves, Abdel-rahman Mohamed, Geoffrey Hinton
Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs…
Discovering Multiple Constraints that are Frequently Approximately Satisfied
Geoffrey E. Hinton, Yee Whye Teh
Some high-dimensional data.sets can be modelled by assuming that there are many different linear constraints, each of which is Frequently Approximately Satisfied (FAS) by the data.…