SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 351–360 of 3304 papers

TitleStatusHype
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
A Knowledge-based Representation for Cross-Language Document Retrieval and Categorization—0
Data-Driven Prediction of Dynamic Interactions Between Robot Appendage and Granular Material—0
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy—0
A Kernelization-Based Approach to Nonparametric Binary Choice Models—0
Adapting Speaker Embeddings for Speaker Diarisation—0
Asteroids co-orbital motion classification based on Machine Learning—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction—0
A Stable Measure for Conditional Periodicity of Time Series using Persistent Homology—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