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 1081–1090 of 3304 papers

TitleStatusHype
Diffeomorphic brain shape modelling using Gauss-Newton optimisation—0
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers—0
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization—0
Attention-based Supply-Demand Prediction for Autonomous Vehicles—0
Dictionary Learning under Symmetries via Group Representations—0
A t-SNE Based Classification Approach to Compositional Microbiome Data—0
A mechanism-driven reinforcement learning framework for shape optimization of airfoils—0
A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing—0
Accuracy and Privacy Evaluations of Collaborative Data Analysis—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