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 126–150 of 3304 papers

TitleStatusHype
A preprocessing perspective for quantum machine learning classification advantage using NISQ algorithmsCode1
Adversarial AutoencodersCode1
An efficient aggregation method for the symbolic representation of temporal dataCode1
An Embedding is Worth a Thousand Noisy LabelsCode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
A local approach to parameter space reduction for regression and classification tasksCode1
Approximating Likelihood Ratios with Calibrated Discriminative ClassifiersCode1
A Primer on the Signature Method in Machine LearningCode1
On Path Integration of Grid Cells: Group Representation and Isotropic ScalingCode1
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breathCode1
ATD: Augmenting CP Tensor Decomposition by Self SupervisionCode1
Autoencoding with a Classifier SystemCode1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
Bayesian Optimization of Sampling Densities in MRICode1
BayesOpt Adversarial AttackCode1
A hyperparameter-tuning approach to automated inverse planningCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional DatasetsCode1
The Signature Kernel is the solution of a Goursat PDECode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
An Additive Autoencoder for Dimension EstimationCode1
Show:102550
← PrevPage 6 of 133Next →
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