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 1671–1680 of 3304 papers

TitleStatusHype
One-bit LFMCW Radar: Spectrum Analysis and Target Detection—0
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks—0
On latent dynamics learning in nonlinear reduced order modeling—0
Online Adaptive Mahalanobis Distance Estimation—0
Online Censoring for Large-Scale Regressions with Application to Streaming Big Data—0
Online Distributed Estimation of Principal Eigenspaces—0
Online Kernel Sliced Inverse Regression—0
Online Learning for Supervised Dimension Reduction—0
Online model learning with data-assimilated reservoir computers—0
Online Multi-Label Classification: A Label Compression Method—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