SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1011–1020 of 3304 papers

TitleStatusHype
Distributed Principal Subspace Analysis for Partitioned Big Data: Algorithms, Analysis, and Implementation—0
BDEC:Brain Deep Embedded Clustering model—0
Beam-Space MIMO Radar for Joint Communication and Sensing with OTFS Modulation—0
Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization—0
Distributionally Robust Fair Principal Components via Geodesic Descents—0
Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction—0
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks—0
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein—0
Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables—0
Effective Discriminative Feature Selection with Non-trivial Solutions—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