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 2001–2010 of 3304 papers

TitleStatusHype
Coupled Control Systems: Periodic Orbit Generation with Application to Quadrupedal Locomotion—0
Gaze-Sensing LEDs for Head Mounted Displays—0
Unsupervised machine learning of quantum phase transitions using diffusion maps—0
Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters—0
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—0
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier DetectionCode1
Multivariate Functional Regression via Nested Reduced-Rank Regularization—0
Multi-Scale Superpatch Matching using Dual Superpixel Descriptors—0
Supervised Domain Adaptation using Graph EmbeddingCode1
Xtreaming: an incremental multidimensional projection technique and its application to streaming data—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