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 1021–1030 of 3304 papers

TitleStatusHype
Distribution-based Label Space Transformation for Multi-label Learning—0
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction—0
An Image-Based Fluid Surface Pattern Model—0
Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection—0
CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes—0
Circular Coordinate Methods with Generalized Penalty Functions—0
Angular Embedding: A New Angular Robust Principal Component Analysis—0
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization—0
Circuit design in biology and machine learning. II. Anomaly detection—0
Chiron: A Robust Recommendation System with Graph Regularizer—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