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 1601–1610 of 3304 papers

TitleStatusHype
Implicit Sparse Code Hashing—0
Improved Dimensionality Reduction for Inverse Problems in Nuclear Fusion and High-Energy Astrophysics—0
Brain Inspired Face Recognition: A Computational Framework—0
Improved Gaussian-Bernoulli Restricted Boltzmann Machines for UAV-Ground Communication Systems—0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer—0
Efficient Binary Embedding of Categorical Data using BinSketch—0
Improving evaluation and optimization of MT systems against MEANT—0
Improving information retrieval through correspondence analysis instead of latent semantic analysis—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—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