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Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 3051–3075 of 3304 papers

TitleStatusHype
Adaptive Randomized Dimension Reduction on Massive Data—0
Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors - Extended Version—0
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks—0
Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation—0
Generalized Categorization Axioms—0
Cross-validation of matching correlation analysis by resampling matching weights—0
An Item-Based Collaborative Filtering using Dimensionality Reduction Techniques on Mahout Framework—0
Unsupervised model compression for multilayer bootstrap networks—0
Reduced Basis Decomposition: a Certified and Fast Lossy Data Compression Algorithm—0
Hypoelliptic Diffusion Maps I: Tangent Bundles—0
Functional Inverse Regression in an Enlarged Dimension Reduction Space—0
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA—0
Diverse Landmark Sampling from Determinantal Point Processes for Scalable Manifold Learning—0
Scalable Iterative Algorithm for Robust Subspace Clustering—0
Puzzle Imaging: Using Large-scale Dimensionality Reduction Algorithms for Localization—0
On Convolutional Approximations to Linear Dimensionality Reduction Operators for Large Scale Data Processing—0
Sparse Multivariate Factor Regression—0
On the consistency theory of high dimensional variable screening—0
The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction—0
Personalising Mobile Advertising Based on Users Installed Apps—0
A Confident Information First Principle for Parametric Reduction and Model Selection of Boltzmann Machines—0
Laplacian Mixture Modeling for Network Analysis and Unsupervised Learning on Graphs—0
Optimized Projection for Sparse Representation Based Classification—0
SHOE: Supervised Hashing with Output Embeddings—0
IT-map: an Effective Nonlinear Dimensionality Reduction Method for Interactive Clustering—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified