Skip to search formSkip to main contentSkip to account menu

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… 
Wikipedia (opens in a new tab)

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.
2017
2017
Neural-based Context Representation Learning for Dialog Act Classification
We explore context representation learning methods in neural-based models for dialog act classification. We propose and compare… 
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… 
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… 
2014
2014
Distributed representations for compositional semantics
The mathematical representation of semantics is a key issue for Natural Language Processing (NLP). A lot of research has been… 
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… 
2005
2005
Mode-coupling control and new index profile of GI POF for restricted-launch condition in very-short-reach networks
This paper confirms that numerical aperture (NA) is a key factor in mode coupling [the energy transfer among propagating modes in… 
2005
2005
Propagating mode analysis and design of waveguide parameters of GI POF for very short-reach network use
We investigated the way to reduce the mode coupling (the energy transfer among the propagating modes) in a multimode fiber. It… 
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… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)