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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2701–2725 of 3304 papers

TitleStatusHype
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction—0
Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images—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
Joint Dimensionality Reduction and Metric Learning: A Geometric Take—0
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?—0
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation—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
Topology Analysis of International Networks Based on Debates in the United Nations—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