SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 511–520 of 3304 papers

TitleStatusHype
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
Simultaneous Dimensionality Reduction for Extracting Useful Representations of Large Empirical Multimodal Datasets—0
Enhancing literature review with LLM and NLP methods. Algorithmic trading case—0
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation—0
Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skins—0
MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering—0
A Kernelization-Based Approach to Nonparametric Binary Choice Models—0
Learning signals defined on graphs with optimal transport and Gaussian process regression—0
Unsupervised feature selection algorithm framework based on neighborhood interval disturbance fusion—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