SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2831–2840 of 3304 papers

TitleStatusHype
SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives—0
Dimensionality Reduction of Massive Sparse Datasets Using Coresets—0
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity—0
LSTM Autoencoders for Dialect Analysis—0
Large Margin Discriminant Dimensionality Reduction in Prediction Space—0
Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures—0
Image-based localization using LSTMs for structured feature correlation—0
ResFeats: Residual Network Based Features for Image Classification—0
Scalable Adaptive Stochastic Optimization Using Random Projections—0
Firing Rate Dynamics in Recurrent Spiking Neural Networks with Intrinsic and Network Heterogeneity—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