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 851–875 of 3304 papers

TitleStatusHype
Federated Multilinear Principal Component Analysis with Applications in Prognostics—0
Speeding up astrochemical reaction networks with autoencoders and neural ODEsCode0
A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model—0
Economic Forecasts Using Many Noises—0
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion—0
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood AnalysisCode0
Interpretability Illusions in the Generalization of Simplified Models—0
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems—0
Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network—0
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees—0
Calibrating dimension reduction hyperparameters in the presence of noiseCode0
Analysis and mining of low-carbon and energy-saving tourism data characteristics based on machine learning algorithm—0
Relation between PLS and OLS regression in terms of the eigenvalue distribution of the regressor covariance matrix—0
A ripple in time: a discontinuity in American historyCode0
Linear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments—0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography—0
Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery—0
Unsupervised Learning for Topological Classification of Transportation Networks—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIsCode0
Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes—0
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches—0
Bounds on Representation-Induced Confounding Bias for Treatment Effect EstimationCode0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—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