SOTAVerified

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 2301–2350 of 3304 papers

TitleStatusHype
LSTM Autoencoders for Dialect Analysis—0
Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors—0
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models—0
Machine-Learned HASDM Model with Uncertainty Quantification—0
Machine Learning and Factor-Based Portfolio Optimization—0
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction—0
Machine Learning-Based Prediction of Key Genes Correlated to the Subretinal Lesion Severity in a Mouse Model of Age-Related Macular Degeneration—0
Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review—0
Machine learning for assessing quality of service in the hospitality sector based on customer reviews—0
Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis—0
Machine learning in APOGEE: Identification of stellar populations through chemical abundances—0
Machine Learning in LiDAR 3D point clouds—0
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space—0
Machine Learning of coarse-grained Molecular Dynamics Force Fields—0
Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites—0
Machine-Learning the Classification of Spacetimes—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
Macroscopic Market Making Games via Multidimensional Decoupling Field—0
Making Laplacians commute—0
Manifold Approximation by Moving Least-Squares Projection (MMLS)—0
Manifold Fitting in Ambient Space—0
Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias—0
Manifold Learning via Manifold Deflation—0
Manifold learning via quantum dynamics—0
Manifold learning: what, how, and why—0
Manifold Partition Discriminant Analysis—0
Manopt, a Matlab toolbox for optimization on manifolds—0
Mapping Hymns and Organizing Concepts in the Rigveda: Quantitatively Connecting the Vedic Suktas—0
Markov Boundary Discovery with Ridge Regularized Linear Models—0
Massively-Parallel Heat Map Sorting and Applications To Explainable Clustering—0
MASS-UMAP: Fast and accurate analog ensemble search in weather radar archive—0
Mathematical Analysis on Out-of-Sample Extensions—0
Matrix Decomposition on Graphs: A Functional View—0
Matrix Factorization for Inferring Associations and Missing Links—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling—0
Matrix Product Operator Restricted Boltzmann Machines—0
Maximally Correlated Principal Component Analysis—0
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data—0
Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data—0
Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation—0
Maximum Margin Principal Components—0
May the force be with you—0
Measures of Entropy from Data Using Infinitely Divisible Kernels—0
Measuring and modeling the motor system with machine learning—0
Measuring group-separability in geometrical space for evaluation of pattern recognition and embedding algorithms—0
Measuring inter-cluster similarities with Alpha Shape TRIangulation in loCal Subspaces (ASTRICS) facilitates visualization and clustering of high-dimensional data—0
Towards Measuring Place Function Similarity at Fine Spatial Granularity with Trajectory Embedding—0
Measuring the Data—0
Mechanisms of dimensionality reduction and decorrelation in deep neural networks—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