SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 401425 of 3304 papers

TitleStatusHype
Feature Learning for Fault Detection in High-Dimensional Condition-Monitoring SignalsCode0
A Statistical View of Column Subset SelectionCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
A Perturbation-Based Kernel Approximation FrameworkCode0
FibeRed: Fiberwise Dimensionality Reduction of Topologically Complex Data with Vector BundlesCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese NetworksCode0
Fisherposes for Human Action Recognition Using Kinect Sensor DataCode0
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature RepresentationCode0
A Graphical Model for Fusing Diverse Microbiome DataCode0
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value RegularizationCode0
From Gameplay to Symbolic Reasoning: Learning SAT Solver Heuristics in the Style of Alpha(Go) ZeroCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
Functional Diffusion MapsCode0
ALPCAHUS: Subspace Clustering for Heteroscedastic DataCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
A Survey on Multi-Task LearningCode0
Game-theoretic Objective Space PlanningCode0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot LayoutsCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
Anticancer Peptides Classification using Kernel Sparse Representation ClassifierCode0
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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