SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2921–2930 of 3304 papers

TitleStatusHype
Subspace Perspective on Canonical Correlation Analysis: Dimension Reduction and Minimax Rates—0
Theano: A Python framework for fast computation of mathematical expressionsCode0
A Comparative Study of Text Preprocessing Approaches for Topic Detection of User Utterances—0
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow—0
Random Projection Estimation of Discrete-Choice Models with Large Choice Sets—0
Phone-based Metric as a Predictor for Basic Personality Traits—0
Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking—0
Optimizing the Information Retrieval Trade-off in Data Visualization Using -Divergence—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