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 1481–1490 of 3304 papers

TitleStatusHype
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
An iterative coordinate descent algorithm to compute sparse low-rank approximations—0
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis SystemsCode0
Machine Learning and Factor-Based Portfolio Optimization—0
Preliminary Steps Towards Federated Sentiment Classification—0
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey—0
A comparison of latent semantic analysis and correspondence analysis of document-term matrices—0
A Deep Signed Directional Distance Function for Object Shape Representation—0
A local approach to parameter space reduction for regression and classification tasksCode1
Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI—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