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T-distributed stochastic neighbor embedding

Known as: T-Distributed Stochastic Neighbour Embedding, T-SNE 
t-distributed stochastic neighbor embedding (t-SNE) is a machine learning algorithm for dimensionality reduction developed by Laurens van der Maaten… (More)
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Topic mentions per year

2014-2018
01220142018

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BioinformaticsComputer securityDeeplearning4jDimensionality reduction
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Related mentions per year

Related mentions per year

1936-2018
19401960198020002020
T-distributed stochastic neighbor embedding
Machine learning
Bioinformatics
Gradient descent
Dimensionality reduction
Computer security

Papers overview

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Review
2018
Review
2018
Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifier
Current satellite imaging technology enables shooting highresolution pictures of the ground. As any other kind of digital images… (More)
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2017
2017
Feature-based characterization of violin timbre
Timbrai quality of historical violins has been discussed for years. In this paper, we show that it is possible to characterize it… (More)
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2017
2017
No More Discrimination: Cross City Adaptation of Road Scene Segmenters Supplementary Material
Figure 1: t-SNE visualization results. For simplicity, we only show the results of the task Cityscapes → Rio. We could clearly… (More)
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2017
2017
Tissue-resident T cells in hepatitis B: A new target for cure?
  • 2017
More than 240 million people worldwide are chronically infected with the hepatitis B virus (HBV) and are at risk of developing… (More)
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2017
2017
Making machine-learning tools accessible to language teachers and other non-techies: T-SNE-lab and rocanr as first examples
Machine learning advancements could greatly benefit the general public. Many programs or even trained weight matrices are… (More)
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2017
2017
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE
T-distributed stochastic neighbor embedding (tSNE) is a popular and prize-winning approach for dimensionality reduction and… (More)
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2016
2016
VMF-SNE: Embedding for spherical data
T-SNE is a well-known approach to embedding high-dimensional data. The basic assumption of t-SNE is that the data are non… (More)
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2016
2016
Android malware detection using 3-level ensemble
With the dramatic increasing ofthe number of Android malware and the technique of avoiding detection being more and more… (More)
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2015
2015
Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses
Feature extraction has gained increasing attention in the field of machine learning, as in order to detect patterns, extract… (More)
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2014
2014
Dimensionality Reduction Based Similarity Visualization for Neural Gas
  • Kadim Tasdemir
  • 2014 IEEE International Conference on Data Mining…
  • 2014
Two commonly used neural networks for vector quantization based analysis of high-dimensional large datasets are the self… (More)
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