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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 926–950 of 3304 papers

TitleStatusHype
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein—0
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization—0
Randomized Dimension Reduction with Statistical Guarantees—0
Subsurface Characterization using Ensemble-based Approaches with Deep Generative ModelsCode0
Statistical physics, Bayesian inference and neural information processing—0
Latent Dynamic Networked System Identification with High-Dimensional Networked Data—0
On the Power of SVD in the Stochastic Block Model—0
Cluster Exploration using Informative Manifold ProjectionsCode0
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Robust Principal Component Analysis using Density Power Divergence—0
Elastic deep autoencoder for text embedding clustering by an improved graph regularization—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
Analysing race and sex bias in brain age prediction—0
O(k)-Equivariant Dimensionality Reduction on Stiefel ManifoldsCode0
Asteroids co-orbital motion classification based on Machine Learning—0
Metastatic Breast Cancer Prognostication Through Multimodal Integration of Dimensionality Reduction Algorithms and Classification Algorithms—0
Interactive Distillation of Large Single-Topic Corpora of Scientific Papers—0
Noise-Augmented Boruta: The Neural Network Perturbation Infusion with Boruta Feature Selection—0
On the Use of the Kantorovich-Rubinstein Distance for Dimensionality Reduction—0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
Bridging Dense and Sparse Maximum Inner Product Search—0
Supervised Stochastic Neighbor Embedding Using Contrastive LearningCode0
Massively-Parallel Heat Map Sorting and Applications To Explainable Clustering—0
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis—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