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 1661–1670 of 3304 papers

TitleStatusHype
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches—0
Offline Handwritten Recognition of Malayalam District Name - A Holistic Approach—0
OFTER: An Online Pipeline for Time Series Forecasting—0
Omics-driven hybrid dynamic modeling of bioprocesses with uncertainty estimation—0
On a Mechanism Framework of Autoencoders—0
On b-bit min-wise hashing for large-scale regression and classification with sparse data—0
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities—0
On Compression Principle and Bayesian Optimization for Neural Networks—0
On Convolutional Approximations to Linear Dimensionality Reduction Operators for Large Scale Data Processing—0
On Distance and Kernel Measures of Conditional Independence—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