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 2701–2750 of 3304 papers

TitleStatusHype
Understanding a Version of Multivariate Symmetric Uncertainty to assist in Feature SelectionCode0
Tensor-Based Classifiers for Hyperspectral Data Analysis—0
On Principal Components Regression, Random Projections, and Column Subsampling—0
Lazy stochastic principal component analysisCode0
Near Optimal Sketching of Low-Rank Tensor Regression—0
Representation Learning on Graphs: Methods and Applications—0
Bayesian nonparametric Principal Component Analysis—0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—0
Transform Invariant Auto-encoder—0
Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images—0
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction—0
On the Suboptimality of Proximal Gradient Descent for ^0 Sparse Approximation—0
A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms—0
Supervised Dimensionality Reduction for Big DataCode0
Word Embeddings as Features for Supervised Coreference Resolution—0
A deep-learning based native-language classification by using a latent semantic analysis for the NLI Shared Task 2017—0
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future PerspectivesCode0
Dynamic Tensor Clustering—0
Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data—0
Integrative analysis reveals disrupted pathways regulated by microRNAs in cancer—0
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE—0
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 Building—0
Simple and Effective Dimensionality Reduction for Word EmbeddingsCode0
Automatic Selection of t-SNE Perplexity—0
How Do People Differ? A Social Media Approach—0
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication—0
A Latent Variable Model for Two-Dimensional Canonical Correlation Analysis and its Variational Inference—0
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?—0
Parameter Free Hierarchical Graph-Based Clustering for Analyzing Continuous Word Embeddings—0
Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarityCode0
Joint Dimensionality Reduction and Metric Learning: A Geometric Take—0
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation—0
Topology Analysis of International Networks Based on Debates in the United Nations—0
Sparse Deep Nonnegative Matrix Factorization—0
A Harmony Search Based Wrapper Feature Selection Method for Holistic Bangla word Recognition—0
A Survey on Multi-Task LearningCode0
SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
Using PCA and Factor Analysis for Dimensionality Reduction of Bio-informatics Data—0
Sketched Subspace Clustering—0
A Nonlinear Dimensionality Reduction Framework Using Smooth Geodesics—0
Structural Learning and Integrative Decomposition of Multi-View Data—0
Discriminative convolutional Fisher vector network for action recognition—0
Algorithms for Approximate Subtropical Matrix Factorization—0
Prediction with Dimension Reduction of Multiple Molecular Data Sources for Patient Survival—0
Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image RetrievalCode0
Predictive Liability Models and Visualizations of High Dimensional Retail Employee Data—0
Accelerated Stochastic Power IterationCode0
High-Performance FPGA Implementation of Equivariant Adaptive Separation via Independence Algorithm for Independent Component 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