SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2851–2860 of 3304 papers

TitleStatusHype
Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations—0
Structured adaptive and random spinners for fast machine learning computations—0
Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases—0
Probabilistic Dimensionality Reduction via Structure Learning—0
Towards K-means-friendly Spaces: Simultaneous Deep Learning and ClusteringCode1
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification—0
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
Towards a Theoretical Analysis of PCA for Heteroscedastic Data—0
Efficient L1-Norm Principal-Component Analysis via Bit Flipping—0
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks—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