SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1591–1600 of 3304 papers

TitleStatusHype
ABC-FL: Anomalous and Benign client Classification in Federated Learning—0
Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey—0
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsCode0
A Hybrid Learning Approach to Detecting Regime Switches in Financial Markets—0
High dimensional Bayesian Optimization Algorithm for Complex System in Time Series—0
An iterative coordinate descent algorithm to compute sparse low-rank approximations—0
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis SystemsCode0
Machine Learning and Factor-Based Portfolio Optimization—0
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey—0
Preliminary Steps Towards Federated Sentiment Classification—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