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 2841–2850 of 3304 papers

TitleStatusHype
Faster variational inducing input Gaussian process classification—0
Generalized BackPropagation, Étude De Cas: Orthogonality—0
Generalisation and Sharing in Triplet Convnets for Sketch based Visual Search—0
Chiron: A Robust Recommendation System with Graph Regularizer—0
Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction—0
Error Metrics for Learning Reliable Manifolds from Streaming Data—0
Policy Search with High-Dimensional Context Variables—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Information-Theoretic Bounds and Approximations in Neural Population Coding—0
Quantum Laplacian Eigenmap—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