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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 1576–1600 of 3304 papers

TitleStatusHype
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
Identifying Chemicals Through Dimensionality Reduction—0
Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data—0
Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics—0
Identifying Layers Susceptible to Adversarial Attacks—0
Identifying manifolds underlying group motion in Vicsek agents—0
Firing Rate Dynamics in Recurrent Spiking Neural Networks with Intrinsic and Network Heterogeneity—0
Finding Significant Features for Few-Shot Learning using Dimensionality Reduction—0
Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models—0
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
"I know it when I see it". Visualization and Intuitive Interpretability—0
Finding Rule-Interpretable Non-Negative Data Representation—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
Image Classification by Feature Dimension Reduction and Graph based Ranking—0
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction—0
Image retrieval method based on CNN and dimension reduction—0
Finding Real-World Orbital Motion Laws from Data—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
Computation of the Maximum Likelihood estimator in low-rank Factor Analysis—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Impact of the composition of feature extraction and class sampling in medicare fraud detection—0
Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
Computational Graph Completion—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