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 2951–3000 of 3304 papers

TitleStatusHype
Capturing the Denoising Effect of PCA via Compression Ratio—0
Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations—0
Compression supports low-dimensional representations of behavior across neural circuits—0
Compressive Feature Learning—0
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Computational Graph Completion—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Computation of the Maximum Likelihood estimator in low-rank Factor Analysis—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test—0
Computing Approximate _p Sensitivities—0
Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm—0
Concept Drift Detection in Federated Networked Systems—0
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons—0
Concise Fuzzy Planar Embedding of Graphs: a Dimensionality Reduction Approach—0
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization—0
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information—0
Cone-Constrained Principal Component Analysis—0
Consistent Estimation of Low-Dimensional Latent Structure in High-Dimensional Data—0
Consistent Representation Learning for High Dimensional Data Analysis—0
Construction of neural networks for realization of localized deep learning—0
Content-Aware Tweet Location Inference using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding—0
Contextual Bandits with Sparse Data in Web setting—0
Contextual Bidirectional Long Short-Term Memory Recurrent Neural Network Language Models: A Generative Approach to Sentiment Analysis—0
Contextual Categorization Enhancement through LLMs Latent-Space—0
Continuum directions for supervised dimension reduction—0
Contrasting Syntagmatic and Paradigmatic Relations: Insights from Distributional Semantic Models—0
Contrastive analysis for scatterplot-based representations of dimensionality reduction—0
Contrastive inverse regression for dimension reduction—0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex—0
Contrastive Multivariate Singular Spectrum Analysis—0
Convergence rates of Kernel Conjugate Gradient for random design regression—0
Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs—0
Convex Optimization Learning of Faithful Euclidean Distance Representations in Nonlinear Dimensionality Reduction—0
Convolutional Autoencoders for Reduced-Order Modeling—0
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial—0
Assessment of convolutional recurrent autoencoder network for learning wave propagation—0
Cooperative Thresholded Lasso for Sparse Linear Bandit—0
Cortical spatio-temporal dimensionality reduction for visual grouping—0
CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data—0
Cost-efficient Gaussian Tensor Network Embeddings for Tensor-structured Inputs—0
Cost-informed dimensionality reduction for structural digital twin technologies—0
Coupled Control Systems: Periodic Orbit Generation with Application to Quadrupedal Locomotion—0
Coupling the reduced-order model and the generative model for an importance sampling estimator—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Covariance matrix preparation for quantum principal component analysis—0
Covering Number of Real Algebraic Varieties and Beyond: Improved Bounds and Applications—0
Cover Learning for Large-Scale Topology Representation—0
Creation of a Deep Convolutional Auto-Encoder in Caffe—0
Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach—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