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Laurens van der Maaten – Laurens van der Maaten

Laurens van der Maaten

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Laurens van der Maaten – Laurens van der Maaten | lvdmaaten.github.io Reviews

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Laurens van der Maaten

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Curriculum Vitae – Laurens van der Maaten

http://lvdmaaten.github.io/cv

Laurens van der Maaten. Laurens van der Maaten. Research scientist in machine learning and computer vision. I am currently a Research Scientist in Yann LeCun. S team at Facebook AI Research. In New York. Before, I worked as an Assistant Professor at Delft University of Technology. To which I am still affiliated), and as a post-doctoral researcher under supervision of Lawrence Saul. At University of California, San Diego. I received my Ph.D. from Tilburg University. And Jaap van den Herik.

2

Publications – Laurens van der Maaten

http://lvdmaaten.github.io/publications

Laurens van der Maaten. Laurens van der Maaten. Research scientist in machine learning and computer vision. For an overview of citations of my paper, please view my Google Scholar profile. A Joulin*, L.J.P. van der Maaten*, A. Jabri, and N. Vasilache (*both authors contributed equally). Learning Visual Features from Large Weakly Supervised Data. Proceedings of the European Conference on Computer Vision (ECCV). Supplemental material (64 MB). IEEE Signal Processing Magazine. Proceedings of the European Con...

3

Matlab Toolbox for Dimensionality Reduction – Laurens van der Maaten

http://lvdmaaten.github.io/drtoolbox

Laurens van der Maaten. Laurens van der Maaten. Research scientist in machine learning and computer vision. Matlab Toolbox for Dimensionality Reduction. Currently, the Matlab Toolbox for Dimensionality Reduction contains the following techniques:. Principal Component Analysis (PCA). Classical multidimensional scaling (MDS). Linear Discriminant Analysis (LDA). Local Linear Embedding (LLE). Local Tangent Space Alignment (LTSA). Conformal Eigenmaps (extension of LLE). Generalized Discriminant Analysis (GDA).

4

Software – Laurens van der Maaten

http://lvdmaaten.github.io/software

Laurens van der Maaten. Laurens van der Maaten. Research scientist in machine learning and computer vision. This page gives an overview of all the software I have released as open-source over the years. All software on this webpage is free and open source software, distributed under the FreeBSD License. Is available in a wide variety of programming languages here. The code corresponds to the following papers:. LJP van der Maaten. Accelerating t-SNE using Tree-Based Algorithms. For implementations of t-SN...

5

t-SNE – Laurens van der Maaten

http://lvdmaaten.github.io/tsne

Laurens van der Maaten. Laurens van der Maaten. Research scientist in machine learning and computer vision. T-Distributed Stochastic Neighbor Embedding (t-SNE) is a ( prize-winning. LJP van der Maaten. Accelerating t-SNE using Tree-Based Algorithms. Journal of Machine Learning Research. LJP van der Maaten and G.E. Hinton. Visualizing Non-Metric Similarities in Multiple Maps. LJP van der Maaten. Learning a Parametric Embedding by Preserving Local Structure. Journal of Machine Learning Research. Below, imp...

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vbmis | Virtual Biomedical Informatics Learning

http://www.vbmis.com/learn

Virtual Biomedical Informatics Learning. Validation and Parameter Selection. T-Distributed Stochastic Neighbor Embedding. 3 January, 2015 1:42 am. What do we want to do? We want to visualize similarities in high dimensional data. Why should we care? I want to learn about a particular dimensionality reduction algorithm. That works very well with identifying patterns in large datasets, and integrates well into a visualization, t-SNE. I will talk about this algorithm in the context of brain maps. For humans...

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