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Feature learning

Known as: Learning representation, Representation learning, Unsupervised feature learning 
In machine learning, feature learning or representation learning is a set of techniques that learn a feature: a transformation of raw data input to a… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
This paper describes the results of NILC team at CWI 2018. We developed solutions following three approaches: (i) a feature… 
2016
2016
Human pose estimation is a well-known computer vision problem that receives intensive research interest. The reason for such… 
2016
2016
This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input… 
2015
2015
In this paper we propose a method for estimating depth from a single image using a coarse to fine approach. We argue that… 
2015
2015
In this paper, we use deep representation learning for model-based single-channel source separation (SCSS) and artificial… 
2014
2014
Reconfigurable multiple-input multiple-output (MIMO) antennas have the potential to improve the performance of a MIMO antenna… 
2014
2014
Recent work on learning multilingual word representations usually relies on the use of word-level alignements (e.g. infered with… 
2013
2013
This article presents a new global approach for detecting vanishing points and groups of mutually orthogonal vanishing directions… 
2013
2013
  • S. Clark
  • 2013
  • Corpus ID: 11634729
A draft chapter for the OUP book on Compositional methods in Physics and Linguistics. This draft formatted on 27th February 2012. 
2011
2011
Achieving fast and precise failure localization has long been a highly desired feature in all-optical mesh networks. Monitoring…