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 1291–1300 of 3304 papers

TitleStatusHype
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification—0
Quantum artificial vision for defect detection in manufacturing—0
Deep Learning for Size and Microscope Feature Extraction and Classification in Oral Cancer: Enhanced Convolution Neural Network—0
Learning Interaction Variables and Kernels from Observations of Agent-Based Systems—0
Factor Network Autoregressions—0
Distributed Event-Triggered Nonlinear Fusion Estimation under Resource Constraints—0
EMC2A-Net: An Efficient Multibranch Cross-channel Attention Network for SAR Target Classification—0
Cluster Weighted Model Based on TSNE algorithm for High-Dimensional Data—0
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19Code0
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks—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