SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1676–1700 of 3304 papers

TitleStatusHype
Online Distributed Estimation of Principal Eigenspaces—0
Online Kernel Sliced Inverse Regression—0
Online Learning for Supervised Dimension Reduction—0
Online model learning with data-assimilated reservoir computers—0
Online Multi-Label Classification: A Label Compression Method—0
Online Supervised Subspace Tracking—0
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation—0
On Manifold Hypothesis: Hypersurface Submanifold Embedding Using Osculating Hyperspheres—0
On metric choice in dimension reduction for Fréchet regression—0
On Minimum Trace Factor Analysis - An Old Song Sung to a New Tune—0
On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding—0
On Optimality in ROVir—0
On Principal Components Regression, Random Projections, and Column Subsampling—0
On relative universality, regression operator, and conditional independence—0
On Selecting Distance Metrics in n-Dimensional Normed Vector Spaces of Cells: A Novel Criterion and Similarity Measure Towards Efficient and Accurate Omics Analysis—0
On Sufficient Graphical Models—0
On the Computation and Applications of Large Dense Partial Correlation Networks—0
On the Connection Between Non-negative Matrix Factorization and Latent Dirichlet Allocation—0
On the consistency theory of high dimensional variable screening—0
On the Correspondence between Gaussian Processes and Geometric Harmonics—0
On the dimension of pullback attractors in recurrent neural networks—0
On-the-fly spectral unmixing based on Kalman filtering—0
On the Importance of Distraction-Robust Representations for Robot Learning—0
On the Needs for Rotations in Hypercubic Quantization Hashing—0
On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets—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