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 1641–1650 of 3304 papers

TitleStatusHype
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Information-Theoretic Representation Learning for Positive-Unlabeled Classification—0
Feature Clustering for Support Identification in Extreme Regions—0
Infrastructure-Assisted Collaborative Perception in Automated Valet Parking: A Safety Perspective—0
Injecting Wiktionary to improve token-level contextual representations using contrastive learning—0
Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization—0
In search of the most efficient and memory-saving visualization of high dimensional data—0
Deep topic modeling by multilayer bootstrap network and lasso—0
An Empirical Study on Fault Detection and Root Cause Analysis of Indium Tin Oxide Electrodes by Processing S-parameter Patterns—0
Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems—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