ICLR 2017

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iclr2017:callforpapers [2017/01/12 15:44]
rnogueira
iclr2017:callforpapers [2017/04/19 11:46] (current)
rnogueira
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 ~~NOTOC~~ /* Disable table of Contents*/ ~~NOTOC~~ /* Disable table of Contents*/
  
-========Call For Papers========+========Conference Track - Call For Papers========
 \\ \\
 The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as deep learning and feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. The range of domains to which these techniques apply is also very broad, from vision to speech recognition,​ text understanding,​ gaming, music, etc. The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as deep learning and feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. The range of domains to which these techniques apply is also very broad, from vision to speech recognition,​ text understanding,​ gaming, music, etc.
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 To prepare your submission to ICLR 2017, please use the LaTeX style files provided below: To prepare your submission to ICLR 2017, please use the LaTeX style files provided below:
-  * Conference Track: ​{{:​iclr2017:​iclr2017_stylefiles_conference.zip|}}+  * {{:​iclr2017:​iclr2017_stylefiles_conference.zip|}}
  
  
 +====Note to Poster Presenters====
 +  * Each poster panel is 2 meters large and 1 meter tall. If needed, tape will be provided to fix your poster.
  
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