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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 1776–1800 of 3304 papers

TitleStatusHype
Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations—0
Numerical Exploration of Training Loss Level-Sets in Deep Neural Networks—0
Binary Matrix Factorisation via Column Generation—0
Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women—0
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient DescentCode0
Wheat Crop Yield Prediction Using Deep LSTM Model—0
Uncertainty Quantification of Darcy Flow through Porous Media using Deep Gaussian Process—0
Fuzzy Pooling—0
Going Beyond T-SNE: Exposing whatlies in Text Embeddings—0
Towards Measuring Place Function Similarity at Fine Spatial Granularity with Trajectory Embedding—0
RRScell method for automated single-cell profiling of multiplexed immunofluorescence cancer tissue—0
The Mathematical Foundations of Manifold Learning—0
Deep generative LDACode0
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection—0
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
Deep Manifold Transformation for Nonlinear Dimensionality Reduction—0
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder—0
Nested Grassmannians for Dimensionality Reduction with ApplicationsCode0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Geometry-Aware Hamiltonian Variational Auto-Encoder—0
Tensor Train Random Projection—0
Integrating LEO Satellites and Multi-UAV Reinforcement Learning for Hybrid FSO/RF Non-Terrestrial Networks—0
Sufficient dimension reduction for classification using principal optimal transport directionCode0
Product Manifold LearningCode0
Statistical guarantees for generative models without domination—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