SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2111–2120 of 3304 papers

TitleStatusHype
Collaborative Homomorphic Computation on Data Encrypted under Multiple Keys—0
Manifold Denoising by Nonlinear Robust Principal Component AnalysisCode0
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity—0
Decoding Imagined Speech and Computer Control using Brain Waves—0
An automated approach for task evaluation using EEG signals—0
Graph Convolutional Networks Meet with High Dimensionality ReductionCode0
Auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets—0
Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity—0
Privacy-Preserving Machine Learning Using EtC Images—0
News2vec: News Network Embedding with Subnode Information—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