SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2301–2350 of 3304 papers

TitleStatusHype
Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data—0
Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci—0
Tree-structured multi-stage principal component analysis (TMPCA): theory and applications—0
ForestDSH: A Universal Hash Design for Discrete Probability Distributions—0
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs—0
Trigonometric comparison measure: A feature selection method for text categorization—0
Triplet-Based Wireless Channel Charting: Architecture and Experiments—0
Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning—0
TSLFormer: A Lightweight Transformer Model for Turkish Sign Language Recognition Using Skeletal Landmarks—0
t-SNE, Forceful Colorings and Mean Field Limits—0
T-SNE Is Not Optimized to Reveal Clusters in Data—0
Tuning-Free Disentanglement via Projection—0
Two Approaches to Supervised Image Segmentation—0
Two-sample test based on Self-Organizing Maps—0
Two-Stage Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging—0
UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes—0
UDRN: Unified Dimensional Reduction Neural Network for Feature Selection and Feature Projection—0
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data—0
Ultralow-dimensionality reduction for identifying critical transitions by spatial-temporal PCA—0
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization—0
Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation—0
Uncertainty Quantification of Darcy Flow through Porous Media using Deep Gaussian Process—0
Understanding Aesthetic Evaluation using Deep Learning—0
Understanding and Improving Multi-Sense Word Embeddings via Extended Robust Principal Component Analysis—0
Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle—0
Understanding Brain Dynamics for Color Perception using Wearable EEG headband—0
Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation—0
Understanding Contrastive Learning via Gaussian Mixture Models—0
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment—0
Understanding Memory Modules on Learning Simple Algorithms—0
Deep incremental learning models for financial temporal tabular datasets with distribution shifts—0
Relating tSNE and UMAP to Classical Dimensionality Reduction—0
Unified dimensionality reduction techniques in chronic liver disease detection—0
Unified Framework for Spectral Dimensionality Reduction, Maximum Variance Unfolding, and Kernel Learning By Semidefinite Programming: Tutorial and Survey—0
Uniform Approximations for Randomized Hadamard Transforms with Applications—0
Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey—0
Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis—0
Universality laws for randomized dimension reduction, with applications—0
Universality of macroscopic neuronal dynamics in Caenorhabditis elegans—0
Unlocking NACE Classification Embeddings with OpenAI for Enhanced Analysis and Processing—0
UNO-QA: An Unsupervised Anomaly-Aware Framework with Test-Time Clustering for OCTA Image Quality Assessment—0
Toward Unsupervised Test Scenario Extraction for Automated Driving Systems from Urban Naturalistic Road Traffic Data—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction—0
Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation—0
Unsupervised Bump Hunting Using Principal Components—0
Unsupervised Construction of Knowledge Graphs From Text and Code—0
Unsupervised Data-Driven Nuclei Segmentation For Histology Images—0
Unsupervised Deep Haar Scattering on Graphs—0
Unsupervised Dimension Selection using a Blue Noise Spectrum—0
fMBN-E: Efficient Unsupervised Network Structure Ensemble and Selection for Clustering—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