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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 1076–1100 of 3304 papers

TitleStatusHype
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction—0
Additive Component Analysis—0
Differentially private sliced inverse regression in the federated paradigm—0
Attention or memory? Neurointerpretable agents in space and time—0
Diffeomorphic Dimensionality Reduction—0
Diffeomorphic brain shape modelling using Gauss-Newton optimisation—0
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers—0
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization—0
Attention-based Supply-Demand Prediction for Autonomous Vehicles—0
Dictionary Learning under Symmetries via Group Representations—0
A t-SNE Based Classification Approach to Compositional Microbiome Data—0
A mechanism-driven reinforcement learning framework for shape optimization of airfoils—0
A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing—0
Accuracy and Privacy Evaluations of Collaborative Data Analysis—0
3D Face Recognition with Sparse Spherical Representations—0
Diagnosis of Patients with Viral, Bacterial, and Non-Pneumonia Based on Chest X-Ray Images Using Convolutional Neural Networks—0
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image—0
Diagnosing ADHD from fMRI Scans Using Hidden Markov Models—0
DG-GL: Differential geometry based geometric learning of molecular datasets—0
A Topological "Reading" Lesson: Classification of MNIST using TDA—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
A topological classifier to characterize brain states: When shape matters more than variance—0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—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