SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1575 of 3304 papers

TitleStatusHype
Human Motion Detection Using Sharpened Dimensionality Reduction and Clustering—0
Image patch analysis and clustering of sunspots: a dimensionality reduction approach—0
Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images—0
Hybrid Kronecker Product Decomposition and Approximation—0
Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models—0
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit—0
Efficient Binary Embedding of Categorical Data using BinSketch—0
Hybrid Quantum-Classical Machine Learning for Sentiment Analysis—0
Hybrid Subspace Learning for High-Dimensional Data—0
Hybrid Two-Stage Reconstruction of Multiscale Subsurface Flow with Physics-informed Residual Connected Neural Operator—0
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation—0
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction—0
Hyperspectral Image Analysis in Single-Modal and Multimodal setting using Deep Learning Techniques—0
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification—0
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data—0
Hyperspectral Images Classification and Dimensionality Reduction using spectral interaction and SVM classifier—0
Hyperspectral images classification and Dimensionality Reduction using Homogeneity feature and mutual information—0
Hyperspectral Imaging and Analysis for Sparse Reconstruction and Recognition—0
Hyperspectral Remote Sensing Image Classification Based on Multi-scale Cross Graphic Convolution—0
Hypoelliptic Diffusion Maps I: Tangent Bundles—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—0
A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images—0
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)—0
I-Con: A Unifying Framework for Representation Learning—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—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