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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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Related topics

Related topics

33 relations
Artificial neural networkAutoencoderBasis functionBoltzmann machine

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning
This paper describes the results of NILC team at CWI 2018. We developed solutions following three approaches: (i) a feature… 
2016
2016
Body joints regression using deep convolutional neural networks
Human pose estimation is a well-known computer vision problem that receives intensive research interest. The reason for such… 
2016
2016
Approximate Log-Hilbert-Schmidt Distances between Covariance Operators for Image Classification
This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input… 
2015
2015
Coupled depth learning
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
Representation Learning for Single-Channel Source Separation and Bandwidth Extension
In this paper, we use deep representation learning for model-based single-channel source separation (SCSS) and artificial… 
2014
2014
A Pattern Reconfigurable Chassis-Mode MIMO Antenna
Reconfigurable multiple-input multiple-output (MIMO) antennas have the potential to improve the performance of a MIMO antenna… 
2014
2014
Learning Multilingual Word Representations using a Bag-of-Words Autoencoder
Recent work on learning multilingual word representations usually relies on the use of word-level alignements (e.g. infered with… 
2012
2012
Network-Wide Local Unambiguous Failure Localization (NWL-UFL) via Monitoring Trails
Monitoring trail (m-trail) has been proposed as an effective approach for link failure localization in all-optical wavelength… 
2011
2011
A Novel Approach for Failure Localization in All-Optical Mesh Networks
Achieving fast and precise failure localization has long been a highly desired feature in all-optical mesh networks. Monitoring… 
Highly Cited
1989
Highly Cited
1989
Meiosis Networks
A central problem in connectionist modelling is the control of network and architectural resources during learning. In the… 
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