SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 27012725 of 3304 papers

TitleStatusHype
Understanding a Version of Multivariate Symmetric Uncertainty to assist in Feature SelectionCode0
Tensor-Based Classifiers for Hyperspectral Data Analysis0
On Principal Components Regression, Random Projections, and Column Subsampling0
Lazy stochastic principal component analysisCode0
Near Optimal Sketching of Low-Rank Tensor Regression0
Representation Learning on Graphs: Methods and Applications0
Bayesian nonparametric Principal Component Analysis0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems0
Transform Invariant Auto-encoder0
Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images0
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction0
On the Suboptimality of Proximal Gradient Descent for ^0 Sparse Approximation0
A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms0
Supervised Dimensionality Reduction for Big DataCode0
Word Embeddings as Features for Supervised Coreference Resolution0
A deep-learning based native-language classification by using a latent semantic analysis for the NLI Shared Task 20170
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future PerspectivesCode0
Dynamic Tensor Clustering0
Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data0
Integrative analysis reveals disrupted pathways regulated by microRNAs in cancer0
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE0
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute ModelsCode0
Multi-Stage Feature Selection Based Intelligent Classifier for Classification of Incipient Stage Fire in Building0
Simple and Effective Dimensionality Reduction for Word EmbeddingsCode0
Automatic Selection of t-SNE Perplexity0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified