SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1621–1630 of 3304 papers

TitleStatusHype
Imputation of Time-varying Edge Flows in Graphs by Multilinear Kernel Regression and Manifold Learning—0
IMU-based Modularized Wearable Device for Human Motion Classification—0
Incentives and co-evolution: Steering linear dynamical systems with noncooperative agents—0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
Incomplete Pivoted QR-based Dimensionality Reduction—0
Deep neural networks for the evaluation and design of photonic devices—0
A study of semantic augmentation of word embeddings for extractive summarization—0
Incremental Ensemble Gaussian Processes—0
Generalizing Correspondence Analysis for Applications in Machine Learning—0
A Comparative Study of Text Preprocessing Approaches for Topic Detection of User Utterances—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