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.
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… 
2017
2017
Learning emotion-discriminative and domain-invariant features for domain adaptation in speech emotion recognition
2016
2016
Story Cloze Evaluator: Vector Space Representation Evaluation by Predicting What Happens Next
The main intrinsic evaluation for vector space representation has been focused on textual similarity, where the task is to… 
Highly Cited
2015
Highly Cited
2015
Coupled Discriminative Feature Learning for Heterogeneous Face Recognition
This paper presents a coupled discriminative feature learning (CDFL) method for heterogeneous face recognition (HFR). Different… 
Highly Cited
2015
Highly Cited
2015
Learning Word Representations by Jointly Modeling Syntagmatic and Paradigmatic Relations
Vector space representation of words has been widely used to capture fine-grained linguistic regularities, and proven to be… 
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… 
2013
2013
A Global Approach for the Detection of Vanishing Points and Mutually Orthogonal Vanishing Directions
This article presents a new global approach for detecting vanishing points and groups of mutually orthogonal vanishing directions… 
2010
2010
Exploring Representation-Learning Approaches to Domain Adaptation
Most supervised language processing systems show a significant drop-off in performance when they are tested on text that comes… 
Highly Cited
2004
Highly Cited
2004
Real-time object tracking for soccer-robots without color information
Highly Cited
1997
Highly Cited
1997
A Machine Learning Approach to Musical Style Recognition
Much of the work on perception and understanding of music by computers has focused on low-level perceptual features such as pitch… 
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)