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I'm interested in using GAN as a method to make authorship attribution more robust. Using complex NN models (let's say, LSTM) doesn't give much better results
by woliveirajr 8y ago
I'm interested in using GAN as a method to make authorship attribution more robust.
Using complex NN models (let's say, LSTM) doesn't give much better results than simple neurons with deep layers. Seems that the model extraction (how to represent some author style) is the only point that matters, and it then easily forged (i.e., not hard to reproduce the desired style on purpose).
I'm trying to use GAN as a mean of desconstruction, of removal of the ease patterns to see if some NN can use subtle characteristics to identify the author.
- tasdfqwer0897 8y agoSo you are worried that your existing attribution method is too focused on 'obvious' attributes and you want to see if you can make it focus on less obvious things? IIUC, that's something that's been looked at in the ML Fairness literature. See this paper for example: http://www.aies-conference.com/wp-content/papers/main/AIES_2018_paper_162.pdf http://www.aies-conference.com/wp-content/papers/main/AIES_2...