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 2931–2940 of 3304 papers

TitleStatusHype
Phone-based Metric as a Predictor for Basic Personality Traits—0
Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking—0
Optimizing the Information Retrieval Trade-off in Data Visualization Using -Divergence—0
A generalized flow for multi-class and binary classification tasks: An Azure ML approach—0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
A Reconfigurable Low Power High Throughput Architecture for Deep Network Training—0
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data—0
Show:102550
← PrevPage 294 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