SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2291–2300 of 3304 papers

TitleStatusHype
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction—0
Low Dimensional Dynamics of Globally Coupled Complex Riccati Equations: Exact Firing-rate Equations for Spiking Neurons with Clustered Substructure—0
Low-Dimensional Gradient Helps Out-of-Distribution Detection—0
Low-Dimensional Representation-Driven TSK Fuzzy System for Feature Selection—0
Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions—0
Low-Rank Boolean Matrix Approximation by Integer Programming—0
Low-Rank Isomap Algorithm—0
Low-Rank Nonlinear Decoding of μ-ECoG from the Primary Auditory Cortex—0
Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling—0
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack—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