SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 81–90 of 3304 papers

TitleStatusHype
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis—0
A Survey on Archetypal Analysis—0
Generalized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observationsCode0
Effective dimensionality reduction for Greeks computation using Randomized QMC—0
On relative universality, regression operator, and conditional independence—0
InfoClus: Informative Clustering of High-dimensional Data Embeddings—0
Progressive Rock Music Classification—0
SPreV—0
An Incremental Non-Linear Manifold Approximation Method—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