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 526–550 of 3304 papers

TitleStatusHype
Uncovering Temporal Patterns in Visualizations of High-Dimensional Data—0
Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons—0
Representatividad Muestral en la Incertidumbre Simétrica Multivariada para la Selección de Atributos—0
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation ModelsCode0
Targeted Visualization of the Backbone of Encoder LLMsCode1
Assessing the similarity of real matrices with arbitrary shapeCode0
S+t-SNE -- Bringing Dimensionality Reduction to Data StreamsCode0
FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data—0
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer CompressionCode1
Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled Autoencoder for Mixed Tabular Datasets—0
Multiple-Input Auto-Encoder Guided Feature Selection for IoT Intrusion Detection Systems—0
Frequency-dependent covariance reveals critical spatio-temporal patterns of synchronized activity in the human brain—0
A Wasserstein perspective of Vanilla GANs—0
Infrastructure-Assisted Collaborative Perception in Automated Valet Parking: A Safety Perspective—0
Text Clustering with Large Language Model Embeddings—0
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
Curvature Augmented Manifold Embedding and LearningCode0
Evaluating Unsupervised Dimensionality Reduction Methods for Pretrained Sentence Embeddings—0
Temporally-Consistent Koopman Autoencoders for Forecasting Dynamical Systems—0
Discover and Mitigate Multiple Biased Subgroups in Image ClassifiersCode2
Light Curve Classification with DistClassiPy: a new distance-based classifierCode1
Graph Regularized NMF with L20-norm for Unsupervised Feature Learning—0
Enhancing IoT Security Against DDoS Attacks through Federated Learning—0
SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different LanguagesCode0
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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