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 2481–2490 of 3304 papers

TitleStatusHype
A note on concentration inequality for vector-valued martingales with weak exponential-type tails—0
Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data—0
Geometry of Deep Learning for Magnetic Resonance Fingerprinting—0
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
Scalable Manifold Learning for Big Data with Apache SparkCode0
Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti—0
A DEEP ADVERSARIAL LEARNING METHODOLOGY FOR DESIGNING MICROSTRUCTURAL MATERIAL SYSTEMSCode0
Parameter-wise co-clustering for high-dimensional data—0
XPCA: Extending PCA for a Combination of Discrete and Continuous Variables—0
Show:102550
← PrevPage 249 of 331Next →
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