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 651–675 of 3304 papers

TitleStatusHype
Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations—0
Compression supports low-dimensional representations of behavior across neural circuits—0
Compressive Feature Learning—0
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
Computational Graph Completion—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Computation of the Maximum Likelihood estimator in low-rank Factor Analysis—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
A novel filter based on three variables mutual information for dimensionality reduction and classification of hyperspectral images—0
Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test—0
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
Computing Approximate _p Sensitivities—0
Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm—0
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
Concept Drift Detection in Federated Networked Systems—0
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons—0
Concise Fuzzy Planar Embedding of Graphs: a Dimensionality Reduction Approach—0
Cross-validation of matching correlation analysis by resampling matching weights—0
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization—0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—0
A case study : Influence of Dimension Reduction on regression trees-based Algorithms -Predicting Aeronautics Loads of a Derivative Aircraft—0
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information—0
Cone-Constrained Principal Component Analysis—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—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