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 521–530 of 3304 papers

TitleStatusHype
Lossless KV Cache Compression to 2%—0
Efficient Sparse PCA via Block-Diagonalization—0
Large data limits and scaling laws for tSNE—0
Approaching Metaheuristic Deep Learning Combos for Automated Data Mining—0
Game Theory Meets Statistical Mechanics in Deep Learning Design—0
EEG-based 90-Degree Turn Intention Detection for Brain-Computer Interface—0
TL-PCA: Transfer Learning of Principal Component Analysis—0
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction—0
Emulators for stellar profiles in binary population modeling—0
Show:102550
← PrevPage 53 of 331Next →
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