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--- papers:tr-bottou-2011 [2016/09/12 09:21]
leonb
+++ papers:tr-bottou-2011 [2016/09/12 09:44] (current)
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 ===== Notes =====
-This documents cite the NEC Labs work of Vincent Etter (2009) which explores the unsupervised learning of recursive sentence representation. This work is now available on [[http://vincent.etter.io/publications/etter2009master.pdf|Vincent's page]] with a local copy {{vincentetter.pdf|here}}. The relevant text is in section 5.
+This documents cite the work of Vincent Etter (2009) carried out during his NEC Labs internship. Vincent's master report is now available on [[http://vincent.etter.io/publications/etter2009master.pdf|his home page]] ({{vincentetter.pdf|local copy}}). Section 5 is an exploration of that were extensively discussed between Ronan Collobert, Jason Weston and I. We had the hope to discover relevant recursive sentence representation in an unsupervised manner. Alas, we found that the shape of the structure of a recursive network has very little impact on its representation abilities, something that was clearly confirmed by [[https://arxiv.org/pdf/1301.2811.pdf|Scheible and Schütze (2013)]] on a sentiment classification task. Even a left-to-right tree (which amounts to using a recurrent neural network in fact) works essentially as well, something that was cleanly confirmed by [[http://arxiv.org/pdf/1506.01057v1.pdf|Li et al. (2015)]] on a broad collection of NLP tasks.  I still had hopes to make it work when I wrote this tech report in 2010. However these two works have convinced me that structure discovery won't happen without a new idea.

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