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 2101–2150 of 3304 papers

TitleStatusHype
A Fully Convolutional Network for MR Fingerprinting—0
TMI: Thermodynamic inference of data manifolds—0
Gradient-based Sparse Principal Component Analysis with Extensions to Online LearningCode0
Event detection in Colombian security Twitter news using fine-grained latent topic analysis—0
Safe squeezing for antisparse codingCode0
The Similarity-Consensus Regularized Multi-view Learning for Dimension Reduction—0
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis—0
Topological Stability: a New Algorithm for Selecting The Nearest Neighbors in Non-Linear Dimensionality Reduction Techniques—0
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data—0
Efficient Fair Principal Component Analysis—0
Collaborative Homomorphic Computation on Data Encrypted under Multiple Keys—0
Manifold Denoising by Nonlinear Robust Principal Component AnalysisCode0
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity—0
Decoding Imagined Speech and Computer Control using Brain Waves—0
An automated approach for task evaluation using EEG signals—0
Graph Convolutional Networks Meet with High Dimensionality ReductionCode0
Auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets—0
Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity—0
Privacy-Preserving Machine Learning Using EtC Images—0
News2vec: News Network Embedding with Subnode Information—0
Solving NMF with smoothness and sparsity constraints using PALMCode0
Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies—0
A Comparison of Neural Network Training Methods for Text Classification—0
Variational Quantum Algorithms for Dimensionality Reduction and Classification—0
Deep topic modeling by multilayer bootstrap network and lasso—0
Unsupervised Boosting-based Autoencoder Ensembles for Outlier DetectionCode0
Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors—0
Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice SeparationCode0
Supervised tensor decomposition with features on multiple modes—0
Supporting Multi-point Fan Design with Dimension ReductionCode0
LEt-SNE: A Hybrid Approach To Data Embedding and Visualization of Hyperspectral ImageryCode0
A Topological "Reading" Lesson: Classification of MNIST using TDA—0
Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data—0
Multiclass spectral feature scaling method for dimensionality reduction—0
Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models—0
Earthmover-based manifold learning for analyzing molecular conformation spacesCode0
Roweis Discriminant Analysis: A Generalized Subspace Learning MethodCode0
Efficient Sketching Algorithm for Sparse Binary Data—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
Hierarchical stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries—0
Elementos da teoria de aprendizagem de máquina supervisionada—0
Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning—0
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
A Comparison Study on Nonlinear Dimension Reduction Methods with Kernel Variations: Visualization, Optimization and Classification—0
Near-Convex Archetypal Analysis—0
Fault Detection Using Nonlinear Low-Dimensional Representation of Sensor Data—0
Specializing Word Embeddings (for Parsing) by Information BottleneckCode0
MASS-UMAP: Fast and accurate analog ensemble search in weather radar archive—0
TriMap: Large-scale Dimensionality Reduction Using TripletsCode0
Order-Preserving Wasserstein Discriminant 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