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 651–660 of 3304 papers

TitleStatusHype
RdimKD: Generic Distillation Paradigm by Dimensionality Reduction—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring—0
Featurizing Koopman Mode Decomposition For Robust ForecastingCode0
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization—0
Federated Multilinear Principal Component Analysis with Applications in Prognostics—0
Speeding up astrochemical reaction networks with autoencoders and neural ODEsCode0
A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model—0
Economic Forecasts Using Many Noises—0
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion—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