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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3101–3125 of 3304 papers

TitleStatusHype
Diffeomorphic brain shape modelling using Gauss-Newton optimisation—0
Diffeomorphic Dimensionality Reduction—0
Differentially private sliced inverse regression in the federated paradigm—0
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm—0
Differential Privacy for Clustering Under Continual Observation—0
Differential Privacy Meets Neural Network Pruning—0
Difficulty in estimating visual information from randomly sampled images—0
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks—0
Diffusion Fingerprints—0
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis—0
Diffusion Maps meet Nyström—0
Diffusion Maps : Using the Semigroup Property for Parameter Tuning—0
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks—0
Digital Fingerprinting of Microstructures—0
DimenFix: A novel meta-dimensionality reduction method for feature preservation—0
Dimensionality-reduced subspace clustering—0
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder—0
Dimensionality Reduction and Classification feature using Mutual Information applied to Hyperspectral Images : A Filter strategy based algorithm—0
Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network—0
Dimensionality reduction, and function approximation of poly(lactic-co-glycolic acid) micro- and nanoparticle dissolution rate—0
Dimensionality Reduction and Motion Clustering during Activities of Daily Living: 3, 4, and 7 Degree-of-Freedom Arm Movements—0
Dimensionality Reduction and Prioritized Exploration for Policy Search—0
Dimensionality Reduction and State Space Systems: Forecasting the US Treasury Yields Using Frequentist and Bayesian VARs—0
Dimensionality Reduction and Wasserstein Stability for Kernel Regression—0
Dimensionality Reduction as Probabilistic Inference—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