SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3251–3260 of 3304 papers

TitleStatusHype
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians—0
EEG-based 90-Degree Turn Intention Detection for Brain-Computer Interface—0
EEG Signal Dimensionality Reduction and Classification using Tensor Decomposition and Deep Convolutional Neural Networks—0
Effective dimensionality reduction for Greeks computation using Randomized QMC—0
Effective Discriminative Feature Selection with Non-trivial Solutions—0
Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection—0
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization—0
Efficient and Scalable Batch Bayesian Optimization Using K-Means—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—0
Efficient Binary Embedding of Categorical Data using BinSketch—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