Conservativeness of untied auto-encoders
June 25, 2015 ยท Declared Dead ยท ๐ AAAI Conference on Artificial Intelligence
"No code URL or promise found in abstract"
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Authors
Daniel Jiwoong Im, Mohamed Ishmael Diwan Belghazi, Roland Memisevic
arXiv ID
1506.07643
Category
cs.LG: Machine Learning
Citations
12
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
Abstract
We discuss necessary and sufficient conditions for an auto-encoder to define a conservative vector field, in which case it is associated with an energy function akin to the unnormalized log-probability of the data. We show that the conditions for conservativeness are more general than for encoder and decoder weights to be the same ("tied weights"), and that they also depend on the form of the hidden unit activation function, but that contractive training criteria, such as denoising, will enforce these conditions locally. Based on these observations, we show how we can use auto-encoders to extract the conservative component of a vector field.
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