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
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Decoding Emotional Experience through Physiological Signal Processing—0
Mixtape Application: Music Map Methodology and Evaluation—0
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering—0
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods—0
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
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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