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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 1826–1850 of 3304 papers

TitleStatusHype
YNU-oxz at SemEval-2020 Task 5: Detecting Counterfactuals Based on Ordered Neurons LSTM and Hierarchical Attention Network—0
Blind signal decomposition of various word embeddings based on join and individual variance explained—0
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit—0
A Simple and Effective Approach to Robust Unsupervised Bilingual Dictionary Induction—0
t-EVA: Time-Efficient t-SNE Video Annotation—0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Manifold Partition Discriminant Analysis—0
Angular Embedding: A New Angular Robust Principal Component Analysis—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Optimizing Offer Sets in Sub-Linear Time—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Strong and weak principles of neural dimension reduction—0
Functorial Manifold Learning—0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
An efficient label-free analyte detection algorithm for time-resolved spectroscopy—0
TDAsweep: A Novel Dimensionality Reduction Method for Image Classification Tasks—0
Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations—0
Binary Matrix Factorisation via Column Generation—0
Numerical Exploration of Training Loss Level-Sets in Deep Neural Networks—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
Uncertainty Quantification of Darcy Flow through Porous Media using Deep Gaussian Process—0
Wheat Crop Yield Prediction Using Deep LSTM Model—0
Fuzzy Pooling—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