SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 301–325 of 3304 papers

TitleStatusHype
A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing—0
Accuracy and Privacy Evaluations of Collaborative Data Analysis—0
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis—0
A Data Quarantine Model to Secure Data in Edge Computing—0
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems—0
Accelerating Vision Transformers Based on Heterogeneous Attention Patterns—0
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data—0
Alternative Channel Charting Techniques in Cellular Wireless Communications—0
A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction—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
Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction—0
Alternating Co-Quantization for Cross-Modal Hashing—0
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
A Dashboard to Analysis and Synthesis of Dimensionality Reduction Methods in Remote Sensing—0
Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy—0
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks—0
A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning—0
Are Latent Factor Regression and Sparse Regression Adequate?—0
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients—0
A Low Effort Approach to Structured CNN Design Using PCA—0
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA—0
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks—0
Adaptive Randomized Dimension Reduction on Massive Data—0
A Probabilistic Graph Coupling View of Dimension Reduction—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