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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… Expand
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BioinformaticsComputer securityDeeplearning4jDimensionality reduction
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Papers overview

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2019
2019
GPU accelerated t-distributed stochastic neighbor embedding
Abstract Modern datasets and models are notoriously difficult to explore and analyze due to their inherent high dimensionality… Expand
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2019
2019
t-Distributed Stochastic Neighbor Embedding Spectral Clustering using higher order approximations
This paper introduces a new topological clustering approach to cluster high dimensional datasets based on t-SNE (Stochastic… Expand
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2018
2018
Lecture 8 – t-Distributed Stochastic Neighbor Embedding
Year Method Author Summary 1901 PCA Karl Pearson First dimensionality reduction technique 2000 Isomap Tenenbaum, de Silva, and… Expand
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2017
2017
t-Distributed stochastic neighbor embedding spectral clustering
This paper introduces a new topological clustering approach to cluster high dimensional datasets based on t-SNE (Stochastic… Expand
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2017
2017
Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding
Many word clouds provide no semantics to the word placement, but use a random layout optimized solely for aesthetic purposes. We… Expand
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2017
2017
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
Abstract. t-distributed Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization that… Expand
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2016
2016
t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom
One of the dimension reduction (DR) methods for data-visualization, t-distributed stochastic neighbor embedding (t-SNE), has… Expand
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Highly Cited
2014
Highly Cited
2014
Accelerating t-SNE using tree-based algorithms
The paper investigates the acceleration of t-SNE--an embedding technique that is commonly used for the visualization of high… Expand
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2010
2010
On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding
Similarity-based embedding is a paradigm that recently gained interest in the field of nonlinear dimensionality reduction. It… Expand
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2009
2009
Heavy-Tailed Symmetric Stochastic Neighbor Embedding
Stochastic Neighbor Embedding (SNE) has shown to be quite promising for data visualization. Currently, the most popular… Expand
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