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Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1600 of 3304 papers

TitleStatusHype
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
Flashlight Search Medial Axis: A Pixel-Free Pore-Network Extraction Algorithm—0
Fitting a Simplicial Complex using a Variation of k-means—0
Hybrid Kronecker Product Decomposition and Approximation—0
Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models—0
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit—0
Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm—0
Computing Approximate _p Sensitivities—0
Hybrid Subspace Learning for High-Dimensional Data—0
Hybrid Two-Stage Reconstruction of Multiscale Subsurface Flow with Physics-informed Residual Connected Neural Operator—0
A Novel method for Schizophrenia classification using nonlinear features and neural networks—0
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction—0
A Graph Based Raman Spectral Processing Technique for Exosome Classification—0
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification—0
First-order bifurcation detection for dynamic complex networks—0
Hyperspectral Images Classification and Dimensionality Reduction using spectral interaction and SVM classifier—0
Hyperspectral images classification and Dimensionality Reduction using Homogeneity feature and mutual information—0
Hyperspectral Imaging and Analysis for Sparse Reconstruction and Recognition—0
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces—0
Hypoelliptic Diffusion Maps I: Tangent Bundles—0
Firm Heterogeneity and Macroeconomic Fluctuations: a Functional VAR model—0
Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test—0
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)—0
I-Con: A Unifying Framework for Representation Learning—0
ICU Patient Deterioration prediction: a Data-Mining Approach—0
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
Identifying Chemicals Through Dimensionality Reduction—0
Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data—0
Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics—0
Identifying Layers Susceptible to Adversarial Attacks—0
Identifying manifolds underlying group motion in Vicsek agents—0
Firing Rate Dynamics in Recurrent Spiking Neural Networks with Intrinsic and Network Heterogeneity—0
Finding Significant Features for Few-Shot Learning using Dimensionality Reduction—0
Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models—0
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
"I know it when I see it". Visualization and Intuitive Interpretability—0
Finding Rule-Interpretable Non-Negative Data Representation—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
A novel filter based on three variables mutual information for dimensionality reduction and classification of hyperspectral images—0
Image Classification by Feature Dimension Reduction and Graph based Ranking—0
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction—0
Image retrieval method based on CNN and dimension reduction—0
Finding Real-World Orbital Motion Laws from Data—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
Computation of the Maximum Likelihood estimator in low-rank Factor Analysis—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Impact of the composition of feature extraction and class sampling in medicare fraud detection—0
Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
Computational Graph Completion—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