SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2581–2590 of 3304 papers

TitleStatusHype
Stock Price Prediction using Principle Components—0
Low-Rank Boolean Matrix Approximation by Integer Programming—0
Interpreting Deep Classifier by Visual Distillation of Dark Knowledge—0
Construction of neural networks for realization of localized deep learning—0
Concise Fuzzy Planar Embedding of Graphs: a Dimensionality Reduction Approach—0
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization—0
On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding—0
Deep Continuous ClusteringCode0
An Analysis of the t-SNE Algorithm for Data Visualization—0
Understanding and Improving Multi-Sense Word Embeddings via Extended Robust Principal Component Analysis—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