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 1261–1270 of 3304 papers

TitleStatusHype
Fast Data-driven Greedy Sensor Selection for Ridge Regression—0
Fast Data-independent KLT Approximations Based on Integer Functions—0
Fast emulation of cosmological density fields based on dimensionality reduction and supervised machine-learning—0
Faster Discovery of Faster System Configurations with Spectral Learning—0
Faster learning of deep stacked autoencoders on multi-core systems using synchronized layer-wise pre-training—0
Faster variational inducing input Gaussian process classification—0
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming—0
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method—0
Fast Multi-Group Gaussian Process Factor Models—0
Bringing Order to Chaos: A Non-Sequential Approach for Browsing Large Sets of Found Audio Data—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