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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 3201–3225 of 3304 papers

TitleStatusHype
Multilingual Summarization: Dimensionality Reduction and a Step Towards Optimal Term Coverage—0
Using Lexical Expansion to Learn Inference Rules from Sparse Data—0
Robust Feature Extraction to Utterance Fluctuation of Articulation Disorders Based on Random Projection—0
Borel Isomorphic Dimensionality Reduction of Data and Supervised Learning—0
Dimension Reduction via Colour Refinement—0
Making Laplacians commute—0
Toward Guaranteed Illumination Models for Non-Convex Objects—0
A non-parametric conditional factor regression model for high-dimensional input and response—0
Robust Support Vector Machines for Speaker Verification Task—0
Flexible sampling of discrete data correlations without the marginal distributions—0
A Novel Approach for Single Gene Selection Using Clustering and Dimensionality Reduction—0
Spectral Convergence of the connection Laplacian from random samples—0
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis—0
Improving Lexical Semantics for Sentential Semantics: Modeling Selectional Preference and Similar Words in a Latent Variable Model—0
Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance—0
Learning Multiple Non-linear Sub-spaces Using K-RBMs—0
Histograms of Sparse Codes for Object Detection—0
Sparse Subspace Denoising for Image Manifolds—0
Local Fisher Discriminant Analysis for Pedestrian Re-identification—0
Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery—0
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
Ensembles of Classifiers based on Dimensionality Reduction—0
Tensor Decompositions: A New Concept in Brain Data Analysis?—0
Inverting Nonlinear Dimensionality Reduction with Scale-Free Radial Basis Function Interpolation—0
Learning Densities Conditional on Many Interacting Features—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