SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 721–730 of 3304 papers

TitleStatusHype
Cross-validation of matching correlation analysis by resampling matching weights—0
CSI Compression using Channel Charting—0
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
CUR Decompositions, Approximations, and Perturbations—0
Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks—0
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning—0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—0
Data augmentation and feature selection for automatic model recommendation in computational physics—0
A Fully Convolutional Network for MR Fingerprinting—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