SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 24412450 of 3304 papers

TitleStatusHype
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis0
The Price of Fair PCA: One Extra DimensionCode0
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds0
Unsupervised Dimension Selection using a Blue Noise Spectrum0
Non-linear Canonical Correlation Analysis: A Compressed Representation Approach0
Contrastive Multivariate Singular Spectrum Analysis0
Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction0
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation0
Scaling Gaussian Process Regression with DerivativesCode0
Failing Loudly: An Empirical Study of Methods for Detecting Dataset ShiftCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified