SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2701–2750 of 3304 papers

TitleStatusHype
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks—0
A note on concentration inequality for vector-valued martingales with weak exponential-type tails—0
A Note on Dimensionality Reduction in Deep Neural Networks using Empirical Interpolation Method—0
A Novel Approach for Dimensionality Reduction and Classification of Hyperspectral Images based on Normalized Synergy—0
A Novel Approach for Intrinsic Dimension Estimation—0
A Novel Approach for Single Gene Selection Using Clustering and Dimensionality Reduction—0
A Novel Bilingual Word Embedding Method for Lexical Translation Using Bilingual Sense Clique—0
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography—0
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
A novel filter based on three variables mutual information for dimensionality reduction and classification of hyperspectral images—0
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
A Novel method for Schizophrenia classification using nonlinear features and neural networks—0
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
Anti-drift in electronic nose via dimensionality reduction: a discriminative subspace projection approach—0
ANTLER: Bayesian Nonlinear Tensor Learning and Modeler for Unstructured, Varying-Size Point Cloud Data—0
A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses—0
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Application of Deep Learning for Predictive Maintenance of Oilfield Equipment—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
Application of Dimensional Reduction in Artificial Neural Networks to Improve Emergency Department Triage During Chemical Mass Casualty Incidents—0
Application of Fuzzy Clustering for Text Data Dimensionality Reduction—0
Application of Symmetric Uncertainty and Mutual Information to Dimensionality Reduction and Classification of Hyperspectral Images—0
Application Research On Real-Time Perception Of Device Performance Status—0
Applications of machine learning to predict seasonal precipitation for East Africa—0
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics—0
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images—0
Applying a random projection algorithm to optimize machine learning model for breast lesion classification—0
Applying Graph-based Keyword Extraction to Document Retrieval—0
Applying Ricci Flow to High Dimensional Manifold Learning—0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
Approaching Metaheuristic Deep Learning Combos for Automated Data Mining—0
Approximated and User Steerable tSNE for Progressive Visual Analytics—0
Approximate Grassmannian Intersections: Subspace-Valued Subspace Learning—0
Approximate Matrix Multiplication with Application to Linear Embeddings—0
Approximation Algorithms for Sparse Principal Component Analysis—0
Approximation of Functions over Manifolds: A Moving Least-Squares Approach—0
A predictive physics-aware hybrid reduced order model for reacting flows—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 Radiomics-Incorporated Deep Ensemble Learning Model for Multi-Parametric MRI-based Glioma Segmentation—0
A Reconfigurable Low Power High Throughput Architecture for Deep Network Training—0
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis—0
Are Latent Factor Regression and Sparse Regression Adequate?—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