SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 601610 of 3304 papers

TitleStatusHype
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient DescentCode0
Efficient Outlier Removal in Large Scale Global Structure-from-MotionCode0
A Computational Topology-based Spatiotemporal Analysis Technique for Honeybee AggregationCode0
Cluster Exploration using Informative Manifold ProjectionsCode0
ClusterGraph: a new tool for visualization and compression of multidimensional dataCode0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue OptimizationCode0
Enhancing Affinity Propagation for Improved Public Sentiment InsightsCode0
Clustering Noisy Signals with Structured Sparsity Using Time-Frequency RepresentationCode0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
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Benchmark Results

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