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 1601–1625 of 3304 papers

TitleStatusHype
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
Improved Dimensionality Reduction for Inverse Problems in Nuclear Fusion and High-Energy Astrophysics—0
A novel filter based on three variables mutual information for dimensionality reduction and classification of hyperspectral images—0
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction—0
Finding Real-World Orbital Motion Laws from Data—0
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
Improving evaluation and optimization of MT systems against MEANT—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
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
FFTLasso: Large-Scale LASSO in the Fourier Domain—0
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction—0
Improving Sparse Representation-Based Classification Using Local Principal Component Analysis—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Agnostically Learning Multi-index Models with Queries—0
Improving the Projection of Global Structures in Data through Spanning Trees—0
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements—0
Imputation of Time-varying Edge Flows in Graphs by Multilinear Kernel Regression and Manifold Learning—0
IMU-based Modularized Wearable Device for Human Motion Classification—0
A Convex Sparse PCA for Feature Analysis—0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
A canonical correlation-based framework for performance analysis of radio access 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