SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 31413150 of 3304 papers

TitleStatusHype
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signalsCode0
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern DataCode0
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value RegularizationCode0
Game-theoretic Objective Space PlanningCode0
An Information Theory-Based Feature Selection Framework for Big Data Under Apache SparkCode0
On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problemsCode0
Asymptotics for Sketching in Least Squares RegressionCode0
On Projections to Linear SubspacesCode0
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components AnalysisCode0
Linear Dimensionality Reduction: Survey, Insights, and GeneralizationsCode0
Show:102550
← PrevPage 315 of 331Next →

Benchmark Results

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