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 351–375 of 3304 papers

TitleStatusHype
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy—0
A Kernelization-Based Approach to Nonparametric Binary Choice Models—0
Adapting Speaker Embeddings for Speaker Diarisation—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction—0
A Survey on Archetypal Analysis—0
AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution—0
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
A Survey on Design-space Dimensionality Reduction Methods for Shape Optimization—0
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
A Hybrid Quantum Classical Pipeline for X Ray Based Fracture Diagnosis—0
Approximation of Functions over Manifolds: A Moving Least-Squares Approach—0
A Hybrid Learning Approach to Detecting Regime Switches in Financial Markets—0
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI—0
A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition—0
Approximation Algorithms for Sparse Principal Component Analysis—0
A Probabilistic Graph Coupling View of Dimension Reduction—0
A probabilistic view on Riemannian machine learning models for SPD matrices—0
A Process for Topic Modelling Via Word Embeddings—0
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks—0
A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model—0
A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning—0
A Hybrid Deep Learning CNN Model for Enhanced COVID-19 Detection from Computed Tomography (CT) Scan Images—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