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Unsupervised learning

Known as: Unsupervised approach, Unsupervised classification 
Unsupervised learning is the machine learning task of inferring a function to describe hidden structure from unlabeled data. Since the examples given… 
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Related topics

Related topics

49 relations
Anomaly detectionArtificial intelligence for video surveillanceAutoencoderAutomatic target recognition

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2011
Highly Cited
2011
Simple Unsupervised Grammar Induction from Raw Text with Cascaded Finite State Models
We consider a new subproblem of unsupervised parsing from raw text, unsupervised partial parsing---the unsupervised version of… 
Highly Cited
2009
Highly Cited
2009
Reducing Semantic Drift with Bagging and Distributional Similarity
Iterative bootstrapping algorithms are typically compared using a single set of hand-picked seeds. However, we demonstrate that… 
Highly Cited
2009
Highly Cited
2009
Word Sequence Models for Single Text Summarization
The main problem for generating an extractive automatic text summary is to detect the most relevant information in the source… 
Highly Cited
2007
Highly Cited
2007
Graph Embedding and Extensions
Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory… 
Highly Cited
2006
Highly Cited
2006
Medical diagnosis as pattern recognition in a framework of information compression by multiple alignment, unification and search
Highly Cited
2003
Highly Cited
2003
Recent improvements in the CU Sonic ASR system for noisy speech: the SPINE task
We report on recent improvements in the University of Colorado system for the DARPA/NRL Speech in Noisy Environments (SPINE) task… 
Highly Cited
2001
Highly Cited
2001
Learning with labeled and unlabeled dataMatthias
Highly Cited
2001
Highly Cited
2001
Video scene change detection method using unsupervised segmentation and object tracking
In order to manage the growing amount of video information efficiently, a video scene change detection method is necessary. Many… 
1997
1997
UNSUPERVISED ROBUST CHANGE DETECTION ON MULTISPECTRAL IMAGERY USING SPECTRAL AND SPATIAL FEATURES
Change detection is a central task for land cover monitoring by remote sensing. It uses multitemporal image data sets in order to… 
Highly Cited
1996
Highly Cited
1996
Iterative unsupervised adaptation using maximum likelihood linear regression
Maximum likelihood linear regression (MLLR) is a parameter transformation technique for both speaker and environment adaptation… 
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