SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 211220 of 3304 papers

TitleStatusHype
DartMinHash: Fast Sketching for Weighted SetsCode1
Curvature-based Feature Selection with Application in Classifying Electronic Health RecordsCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate CurvatureCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Spectral Clustering of Attributed Multi-relational GraphsCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer CompressionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified