SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 861–870 of 3304 papers

TitleStatusHype
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—0
Diagnosis of Patients with Viral, Bacterial, and Non-Pneumonia Based on Chest X-Ray Images Using Convolutional Neural Networks—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—0
Dictionary Learning under Symmetries via Group Representations—0
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization—0
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
Classic machine learning methods—0
Diffeomorphic Dimensionality Reduction—0
Attention or memory? Neurointerpretable agents in space and time—0
An Impossibility Theorem for Node Embedding—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