SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3251–3275 of 3304 papers

TitleStatusHype
A Class-Based Agreement Model for Generating Accurately Inflected Translations—0
Variable noise and dimensionality reduction for sparse Gaussian processes—0
Analyse en Composante Principale pour l'extraction des i-vecteurs en v\'erification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) [in French]—0
Modeling coherence in ESOL learner texts—0
Forecastable Component Analysis (ForeCA)—0
This also affects the context - Errors in extraction based summaries—0
A hierarchical approach with feature selection for emotion recognition from speech—0
Scikit-learn: Machine Learning in PythonCode0
Book Review: Graph-Based Natural Language Processing and Information Retrieval by Rada Mihalcea and Dragomir Radev—0
Demixed Principal Component Analysis—0
Variational Gaussian Process Dynamical Systems—0
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data—0
Dimensionality Reduction Using the Sparse Linear Model—0
Sparse Manifold Clustering and Embedding—0
How to Evaluate Dimensionality Reduction? - Improving the Co-ranking MatrixCode0
Randomized Dimensionality Reduction for k-means Clustering—0
Kernel Methods for the Approximation of Nonlinear Systems—0
Face Recognition using Curvelet Transform—0
Learning Hierarchical Sparse Representations using Iterative Dictionary Learning and Dimension Reduction—0
Vector Diffusion Maps and the Connection LaplacianCode0
Unsupervised Kernel Dimension Reduction—0
Inductive Regularized Learning of Kernel Functions—0
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks—0
Efficient Optimization for Discriminative Latent Class Models—0
Optimal learning rates for Kernel Conjugate Gradient regression—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