tag :: dimensionality-reduction

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1Advanced Algorithm Design Fall 2016 (Statistics)
High Dimensional Statistics by Arora
4 years ago by @kirk86
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1Ordination Methods - an Overview
Differences between PCA, PCoA (MDS), PO and more
5 years ago by @bsc
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2UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction — umap 0.3 documentation
https://umap-learn.readthedocs.io/en/latest/
5 years ago by @bsc
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2NNwebversion.dvi
Independent Component Analysis: Algorithms and Applications
5 years ago by @kirk86
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1Independent Component Analysis: A Tutorial
http://cis.legacy.ics.tkk.fi/aapo/papers/IJCNN99_tutorialweb/
5 years ago by @kirk86
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1Dimensionality reduction: a comparative
L. Van Der Maaten, E. Postma, and J. Van den Herik. J Mach Learn Res, 10 (66-71): 13 (2009)
3 years ago by @salotz
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machine-learning
dimensionality-reductionmachine-learning
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2Learning a Parametric Embedding by Preserving Local Structure.
L. van der Maaten. AISTATS, volume 5 of JMLR Proceedings, page 384-391. JMLR.org, (2009)
4 years ago by @bsc
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6UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
L. McInnes, J. Healy, and J. Melville. (2018)cite arxiv:1802.03426Comment: Reference implementation available at http://github.com/lmcinnes/umap.
4 years ago by @bsc
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visualization
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2With respect to what?: simultaneous interaction with dimension reduction and clustering projections
J. Wenskovitch, M. Dowling, and C. North. Proceedings of the 25th International Conference on Intelligent User Interfaces, ACM, (March 2020)
4 years ago by @brusilovsky
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2Randomly Projected Additive Gaussian Processes for Regression
I. Delbridge, D. Bindel, and A. Wilson. (2019)cite arxiv:1912.12834.
4 years ago by @kirk86
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1Topology Reduction in Deep Convolutional Feature Extraction Networks
T. Wiatowskia, P. Grohsb, and H. Bolcskei. (2016)
4 years ago by @kirk86
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deep-learning
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2Efficient Convex Relaxations for Streaming PCA
R. Arora, and T. Marinov. (2019)
4 years ago by @kirk86
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neurips2019
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3Manifold denoising by Nonlinear Robust Principal Component Analysis
H. Lyu, N. Sha, S. Qin, M. Yan, Y. Xie, and R. Wang. (2019)
4 years ago by @kirk86
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2On Robustness of Principal Component Regression
A. Agarwal, D. Shah, D. Shen, and D. Song. (2019)
4 years ago by @kirk86
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4Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations
D. Kobak, G. Linderman, S. Steinerberger, Y. Kluger, and P. Berens. (2019)
5 years ago by @kirk86
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1Probabilistic Matrix Factorization
R. Salakhutdinov, and A. Mnih. (2004)
5 years ago by @kirk86
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2Separable Layers Enable Structured Efficient Linear Substitutions
G. Gray, E. Crowley, and A. Storkey. (2019)cite arxiv:1906.00859.
5 years ago by @kirk86
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6UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
L. McInnes, J. Healy, and J. Melville. (2018)cite arxiv:1802.03426Comment: Reference implementation available at http://github.com/lmcinnes/umap.
5 years ago by @kirk86
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12Tag recommendations based on tensor dimensionality reduction
P. Symeonidis, A. Nanopoulos, and Y. Manolopoulos. Proceedings of the 2008 ACM conference on Recommender systems, page 43--50. New York, NY, USA, ACM, (2008)
6 years ago by @aho
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3Modeling Social Annotation: a Bayesian Approach
A. Plangprasopchok, and K. Lerman. (May 26, 2010)
6 years ago by @aho
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tagging
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3Exploiting Social Annotation for Automatic Resource Discovery
A. Plangprasopchok, and K. Lerman. (Apr 12, 2007)
6 years ago by @aho
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tagging
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3Collaborative filtering for orkut communities: discovery of user latent behavior
W. Chen, J. Chu, J. Luan, H. Bai, Y. Wang, and E. Chang. Proceedings of the 18th international conference on World wide web, page 681--690. New York, NY, USA, ACM, (2009)
6 years ago by @aho
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3User Recommendations based on Tensor Dimensionality Reduction
P. Symeonidis. Artificial Intelligence Applications and Innovations III, 296, chapter 39, Springer US, Boston, MA, (2009)
6 years ago by @aho
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38Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions
G. Adomavicius, and A. Tuzhilin. Knowledge and Data Engineering, IEEE Transactions on, 17 (6): 734--749 (2005)
6 years ago by @aho
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4An LDA-based Community Structure Discovery Approach for Large-Scale Social Networks
H. Zhang, B. Qiu, C. Giles, H. Foley, and J. Yen. Intelligence and Security Informatics, 2007 IEEE, page 200--207. IEEE, (May 2007)
6 years ago by @aho
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1Advanced Algorithm Design Fall 2016 (Statistics)

1Ordination Methods - an Overview

2UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction — umap 0.3 documentation

2NNwebversion.dvi

1Independent Component Analysis: A Tutorial

publications (hide)33
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1Dimensionality reduction: a comparative

2Learning a Parametric Embedding by Preserving Local Structure.

6UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

2With respect to what?: simultaneous interaction with dimension reduction and clustering projections

2Randomly Projected Additive Gaussian Processes for Regression

1Topology Reduction in Deep Convolutional Feature Extraction Networks

2Efficient Convex Relaxations for Streaming PCA

3Manifold denoising by Nonlinear Robust Principal Component Analysis

2On Robustness of Principal Component Regression

4Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations

1Probabilistic Matrix Factorization

2Separable Layers Enable Structured Efficient Linear Substitutions

6UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

12Tag recommendations based on tensor dimensionality reduction

3Modeling Social Annotation: a Bayesian Approach

3Exploiting Social Annotation for Automatic Resource Discovery

3Collaborative filtering for orkut communities: discovery of user latent behavior

3User Recommendations based on Tensor Dimensionality Reduction

38Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions

4An LDA-based Community Structure Discovery Approach for Large-Scale Social Networks

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