SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2851–2875 of 3304 papers

TitleStatusHype
bigMap: Big Data Mapping with Parallelized t-SNE—0
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery—0
Binary Matrix Factorisation via Column Generation—0
Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
Black-Box k-to-1-PCA Reductions: Theory and Applications—0
Blind signal decomposition of various word embeddings based on join and individual variance explained—0
Block-diagonal covariance selection for high-dimensional Gaussian graphical models—0
Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction—0
Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled Autoencoder for Mixed Tabular Datasets—0
BOLIMES: Boruta and LIME optiMized fEature Selection for Gene Expression Classification—0
Book Review: Graph-Based Natural Language Processing and Information Retrieval by Rada Mihalcea and Dragomir Radev—0
Borel Isomorphic Dimensionality Reduction of Data and Supervised Learning—0
Bounded Manifold Completion—0
Bounds on Causal Effects and Application to High Dimensional Data—0
Brain Inspired Face Recognition: A Computational Framework—0
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
Bridging Dense and Sparse Maximum Inner Product Search—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Bringing Order to Chaos: A Non-Sequential Approach for Browsing Large Sets of Found Audio Data—0
Broadband Beamforming via Linear Embedding—0
Broadcast Product: Shape-aligned Element-wise Multiplication and Beyond—0
Building Models for Biopathway Dynamics Using Intrinsic Dimensionality Analysis—0
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION—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