SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2931–2940 of 3304 papers

TitleStatusHype
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
A Reconfigurable Low Power High Throughput Architecture for Deep Network Training—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data—0
Classification with Repulsion Tensors: A Case Study on Face Recognition—0
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed SystemsCode0
Laplacian Eigenmaps from Sparse, Noisy Similarity Measurements—0
A Primer on the Signature Method in Machine LearningCode1
An Innovative Imputation and Classification Approach for Accurate Disease Prediction—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