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 1576–1600 of 3304 papers

TitleStatusHype
Multi-view Clustering via Deep Matrix Factorization and Partition Alignment—0
Tensor Random Projection for Low Memory Dimension Reduction—0
Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra—0
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential EquationsCode0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data AnalysisCode0
Efficient channel charting via phase-insensitive distance computation—0
A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiologyCode1
On Geodesic Distances and Contextual Embedding Compression for Text ClassificationCode0
Chasing Collective Variables using Autoencoders and biased trajectories—0
Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering TransformsCode1
Towards Exploratory Landscape Analysis for Large-scale Optimization: A Dimensionality Reduction FrameworkCode0
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopyCode0
Compact and Effective Representations for Sketch-based Image Retrieval—0
Quantum algorithms for SVD-based data representation and analysisCode0
Multidimensional Scaling for Gene Sequence Data with Autoencoders—0
Grassmann Iterative Linear Discriminant Analysis with Proxy Matrix Optimization—0
Capturing patterns of variation unique to a specific datasetCode0
Jointly Modeling and Clustering Tensors in High Dimensions—0
Unsupervised low-rank representations for speech emotion recognition—0
Classifying herbal medicine origins by temporal and spectral data mining of electronic noseCode0
Revisiting Bayesian Autoencoders with MCMCCode0
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap—0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Granger Causality Based Hierarchical Time Series Clustering for State Estimation—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