Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs

By Yann Dauphin, Yoshua Bengio. 2013

21 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Chaoyun Zhang
2. Hamed Haddadi
3. Paul Patras
4. Yoshua Bengio
5. Kyunghyun Cho
6. Aaron C. Courville
7. Quoc V. Le
8. Ruslan Salakhutdinov

Citations in the corpus

• How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation (2014, background): “3 of Dauphin and Bengio (2013)), with the i -th input being masked when reconstructing it (similarly to pseudo-likelihood).”
• Deep Learning in Mobile and Wireless Networking: A Survey (2018, background): “forecasting [159], ratio matching [160], and speech recognition [161].”