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 351–360 of 3304 papers

TitleStatusHype
Statistical tuning of artificial neural network—0
Self-Supervised Graph Embedding Clustering—0
Exploring Fine-grained Retail Product Discrimination with Zero-shot Object Classification Using Vision-Language ModelsCode0
FLeNS: Federated Learning with Enhanced Nesterov-Newton SketchCode0
Relevance-driven Decision Making for Safer and More Efficient Human Robot Collaboration—0
Shape-informed surrogate models based on signed distance function domain encoding—0
The Impact of Element Ordering on LM Agent PerformanceCode0
User-friendly Foundation Model Adapters for Multivariate Time Series Classification—0
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction—0
Unlocking NACE Classification Embeddings with OpenAI for Enhanced Analysis and Processing—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