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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 1751–1775 of 3304 papers

TitleStatusHype
YNU-oxz at SemEval-2020 Task 5: Detecting Counterfactuals Based on Ordered Neurons LSTM and Hierarchical Attention Network—0
Consistent Representation Learning for High Dimensional Data Analysis—0
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for AutoencodersCode1
Learning Feature Sparse Principal SubspaceCode0
Learning sparse codes from compressed representations with biologically plausible local wiring constraintsCode0
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction—0
A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies ReconstructionCode0
Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform—0
A Simple and Effective Approach to Robust Unsupervised Bilingual Dictionary Induction—0
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit—0
Blind signal decomposition of various word embeddings based on join and individual variance explained—0
t-EVA: Time-Efficient t-SNE Video Annotation—0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Manifold Partition Discriminant Analysis—0
Locally Linear Embedding and its Variants: Tutorial and SurveyCode1
Angular Embedding: A New Angular Robust Principal Component Analysis—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Optimizing Offer Sets in Sub-Linear Time—0
Strong and weak principles of neural dimension reduction—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Functorial Manifold Learning—0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
An efficient label-free analyte detection algorithm for time-resolved spectroscopy—0
TDAsweep: A Novel Dimensionality Reduction Method for Image Classification Tasks—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