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 2781–2790 of 3304 papers

TitleStatusHype
Distributionally Robust Optimization with Markovian DataCode0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
CNTK: Microsoft's Open-Source Deep-Learning ToolkitCode0
Practical Hash Functions for Similarity Estimation and Dimensionality ReductionCode0
Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice SeparationCode0
SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different LanguagesCode0
Divergence Regulated Encoder Network for Joint Dimensionality Reduction and ClassificationCode0
Improving text classification with vectors of reduced precisionCode0
Degradation Modeling and Prognostic Analysis Under Unknown Failure ModesCode0
DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object DetectionCode0
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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