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Supervised learning

Known as: Fully-supervised machine learning, Supervised Machine Learning, Supervised classification 
Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training… 
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Related topics

Related topics

49 relations
Anomaly detectionBackpropagationBias–variance tradeoffBioinformatics

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2017
Highly Cited
2017
Improving Landmark Localization with Semi-Supervised Learning
We present two techniques to improve landmark localization in images from partially annotated datasets. Our primary goal is to… 
Highly Cited
2016
Highly Cited
2016
Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning
In this paper, we focus on tackling the problem of automatic semantic annotation of high resolution (HR) optical satellite images… 
Highly Cited
2013
Highly Cited
2013
Semi-supervised learning using greedy max-cut
Graph-based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems… 
Highly Cited
2011
Highly Cited
2011
Decision Forests for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning
This paper presents a unified, efficient model of random decision forests which can be applied to a number of machine learning… 
Highly Cited
2010
Highly Cited
2010
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of… 
Highly Cited
2010
Highly Cited
2010
Semi-supervised hashing for scalable image retrieval
Large scale image search has recently attracted considerable attention due to easy availability of huge amounts of data. Several… 
Highly Cited
2007
Highly Cited
2007
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a… 
Highly Cited
2005
Highly Cited
2005
A High-Performance Semi-Supervised Learning Method for Text Chunking
In machine learning, whether one can build a more accurate classifier by using unlabeled data (semi-supervised learning) is an… 
2005
2005
Robust Supervised Learning
Supervised machine learning techniques developed in the Probably Approximately Correct, Maximum A Posteriori, and Structural Risk… 
Highly Cited
1990
Highly Cited
1990
BFGS Optimization for Faster and Automated Supervised Learning
Standard back-propagation learning (BP) is known to have slow convergence properties. Furthermore no general prescription is… 
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