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 1091–1100 of 3304 papers

TitleStatusHype
Efficient Sketching Algorithm for Sparse Binary Data—0
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
Emulators for stellar profiles in binary population modeling—0
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching—0
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION—0
Building Models for Biopathway Dynamics Using Intrinsic Dimensionality Analysis—0
Efficient Optimization for Discriminative Latent Class Models—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX)—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