SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3261–3270 of 3304 papers

TitleStatusHype
Efficient channel charting via phase-insensitive distance computation—0
Efficient Contextual Representation Learning Without Softmax Layer—0
Efficient Design of Hardware-Enabled Reservoir Computing in FPGAs—0
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products—0
Efficient Fair Principal Component Analysis—0
Efficient GPU implementation of randomized SVD and its applications—0
Efficient L1-Norm Principal-Component Analysis via Bit Flipping—0
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
Efficient Learning and Planning with Compressed Predictive States—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