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 1701–1750 of 3304 papers

TitleStatusHype
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study—0
Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA—0
1-Bit Compressive Sensing for Efficient Federated Learning Over the Air—0
High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB—0
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing—0
Model Order Reduction based on Runge-Kutta Neural Network—0
A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction—0
Measuring and modeling the motor system with machine learning—0
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges—0
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack—0
Meta-learning of Pooling Layers for Character RecognitionCode0
On the Whitney near extension problem, BMO, alignment of data, best approximation in algebraic geometry, manifold learning and their beautiful connections: A modern treatmentCode0
Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation—0
Data Discovery Using Lossless Compression-Based Sparse Representation—0
Distributed Principal Subspace Analysis for Partitioned Big Data: Algorithms, Analysis, and Implementation—0
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks—0
Grassmann Graph Embedding—0
Empirical comparison between autoencoders and traditional dimensionality reduction methods—0
Simplicial RegularizationCode0
Low-Rank Isomap Algorithm—0
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS—0
Lazy FSCA for Unsupervised Variable SelectionCode0
FedPower: Privacy-Preserving Distributed Eigenspace Estimation—0
The Mathematics Behind Spectral Clustering And The Equivalence To PCA—0
Unsupervised dynamic modeling of medical image transformationCode0
Validating Clustering Frameworks for Electric Load Demand ProfilesCode0
t-SNE, Forceful Colorings and Mean Field Limits—0
Quantization Algorithms for Random Fourier Features—0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—0
Theoretical Understandings of Product Embedding for E-commerce Machine Learning—0
Learning-Augmented Sketches for Hessians—0
Multi-Space Evolutionary Search for Large-Scale Optimization—0
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized AutoencodersCode0
Center Smoothing: Certified Robustness for Networks with Structured OutputsCode0
A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Random Projections for Improved Adversarial Robustness—0
Joint Characterization of Multiscale Information in High Dimensional Data—0
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning—0
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoderCode0
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
Communication-efficient k-Means for Edge-based Machine Learning—0
RaSE: A Variable Screening Framework via Random Subspace EnsemblesCode0
Direction and Constraint in Phenotypic Evolution: Dimension Reduction and Global Proportionality in Phenotype Fluctuation and Responses—0
Robust Principal Component Analysis: A Median of Means Approach—0
Matrix Decomposition on Graphs: A Functional View—0
Optimizing Unlicensed Band Spectrum Sharing With Subspace-Based Pareto Tracing—0
System-reliability based multi-ensemble of GAN and one-class joint Gaussian distributions for unsupervised real-time structural health monitoring—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