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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… Expand
Wikipedia

Related topics

Related topics

33 relations
Artificial neural networkAutoencoderBasis functionBoltzmann machine
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Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
A survey of the recent architectures of deep convolutional neural networks
Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several… Expand
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Review
2019
Review
2019
Review of Deep Learning Algorithms and Architectures
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as… Expand
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Review
2019
Review
2019
Survey on deep learning with class imbalance
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective… Expand
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Review
2019
Review
2019
Recent Advances of Generative Adversarial Networks in Computer Vision
The appearance of generative adversarial networks (GAN) provides a new approach and framework for computer vision. Compared with… Expand
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Highly Cited
2017
Highly Cited
2017
Adversarial Feature Learning
The ability of the Generative Adversarial Networks (GANs) framework to learn generative models mapping from simple latent… Expand
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Highly Cited
2016
Highly Cited
2016
Context Encoders: Feature Learning by Inpainting
We present an unsupervised visual feature learning algorithm driven by context-based pixel prediction. By analogy with auto… Expand
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Highly Cited
2011
Highly Cited
2011
An Analysis of Single-Layer Networks in Unsupervised Feature Learning
A great deal of research has focused on algorithms for learning features from unlabeled data. Indeed, much progress has been made… Expand
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Highly Cited
2011
Highly Cited
2011
Reading Digits in Natural Images with Unsupervised Feature Learning
Detecting and reading text from natural images is a hard computer vision task that is central to a variety of emerging… Expand
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Highly Cited
2007
Highly Cited
2007
Convex multi-task feature learning
Abstract We present a method for learning sparse representations shared across multiple tasks. This method is a generalization of… Expand
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Highly Cited
2006
Highly Cited
2006
Multi-Task Feature Learning
We present a method for learning a low-dimensional representation which is shared across a set of multiple related tasks. The… Expand
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