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 776–800 of 3304 papers

TitleStatusHype
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognitionCode0
Multi-fidelity reduced-order surrogate modelingCode1
Why do universal adversarial attacks work on large language models?: Geometry might be the answer—0
Dimensionality Reduction Using pseudo-Boolean polynomials For Cluster Analysis—0
Optimal Projections for Discriminative Dictionary Learning using the JL-lemmaCode0
Sparse Models for Machine Learning—0
Class-constrained t-SNE: Combining Data Features and Class ProbabilitiesCode0
The Potential of Quantum Techniques for Stock Price Prediction—0
Is Deep Learning Network Necessary for Image Generation?—0
Free Lunch for Gait Recognition: A Novel Relation Descriptor—0
Ultra Dual-Path Compression For Joint Echo Cancellation And Noise SuppressionCode1
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction—0
An Empirical Study on Fault Detection and Root Cause Analysis of Indium Tin Oxide Electrodes by Processing S-parameter Patterns—0
Rigid Transformations for Stabilized Lower Dimensional Space to Support Subsurface Uncertainty Quantification and InterpretationCode0
Weighted Sparse Partial Least Squares for Joint Sample and Feature SelectionCode0
Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection—0
Deep Learning Architecture for Motor Imaged Words—0
Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review—0
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning ProblemsCode0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Visualization of Extremely Sparse Contingency Table by Taxicab Correspondence Analysis: A Case Study of Textual Data—0
Flashlight Search Medial Axis: A Pixel-Free Pore-Network Extraction Algorithm—0
Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning—0
Regular Variation in Hilbert Spaces and Principal Component Analysis for Functional Extremes—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