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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3231–3240 of 3304 papers

Title	Date	Tasks	Status	Hype
Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion Recognition	Jun 21, 2022	Active LearningClustering	CodeCode Available	0
A Graphical Model for Fusing Diverse Microbiome Data	Aug 21, 2022	Dimensionality Reduction	CodeCode Available	0
Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning	Dec 21, 2020	Dimensionality Reductionreinforcement-learning	CodeCode Available	0
Topology-Preserving Dimensionality Reduction via Interleaving Optimization	Jan 31, 2022	Data VisualizationDimensionality Reduction	CodeCode Available	0
GraphTSNE: A Visualization Technique for Graph-Structured Data	Apr 15, 2019	Dimensionality Reduction	CodeCode Available	0
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding	Mar 2, 2019	CPUDimensionality Reduction	CodeCode Available	0
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddings	Nov 6, 2023	Dimensionality Reduction	CodeCode Available	0
Revisiting Bayesian Autoencoders with MCMC	Apr 13, 2021	Bayesian InferenceDeep Learning	CodeCode Available	0
Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layer	May 2, 2024	Dimensionality ReductionOut-of-Distribution Detection	CodeCode Available	0
Master's Thesis: Out-of-distribution Detection with Energy-based Models	Jan 28, 2023	Autonomous DrivingDimensionality Reduction	CodeCode Available	0

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All datasets MCA EMNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	90.9	—	Unverified
2	tSNE	Classification Accuracy	51.5	—	Unverified
3	IVIS	Classification Accuracy	46.6	—	Unverified
4	UMAP	Classification Accuracy	41.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	71.1	—	Unverified
2	QS	Classification Accuracy	68	—	Unverified