SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2751–2775 of 3304 papers

TitleStatusHype
Feature Hashing for Language and Dialect Identification—0
Skip-Gram − Zipf + Uniform = Vector Additivity—0
Generalized notions of sparsity and restricted isometry property. Part I: A unified framework—0
CatBoost: unbiased boosting with categorical featuresCode0
Efficient Manifold and Subspace Approximations with SphereletsCode0
Improving text classification with vectors of reduced precisionCode0
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network—0
Hidden Talents of the Variational AutoencoderCode0
A survey of dimensionality reduction techniques based on random projection—0
Multi-View Kernels for Low-Dimensional Modeling of Seismic Events—0
Embedding Feature Selection for Large-scale Hierarchical Classification—0
Dimensionality reduction for acoustic vehicle classification with spectral embedding—0
Segmented and Non-Segmented Stacked Denoising Autoencoder for Hyperspectral Band Reduction—0
Linear Dimensionality Reduction in Linear Time: Johnson-Lindenstrauss-type Guarantees for Random Subspace—0
An Investigation of Newton-Sketch and Subsampled Newton Methods—0
Maximum Margin Principal Components—0
Dimensionality reduction, and function approximation of poly(lactic-co-glycolic acid) micro- and nanoparticle dissolution rate—0
DeepRT: deep learning for peptide retention time prediction in proteomics—0
Local Shrunk Discriminant Analysis (LSDA)—0
Pointed subspace approach to incomplete data—0
Offline Handwritten Recognition of Malayalam District Name - A Holistic Approach—0
Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors—0
Expressing Facial Structure and Appearance Information in Frequency Domain for Face Recognition—0
Locality Preserving Projections for Grassmann manifold—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