SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3076–3100 of 3304 papers

TitleStatusHype
Deep Learning with Nonparametric ClusteringCode0
Deep Autoencoders for Dimensionality Reduction of High-Content Screening Data—0
Chainer: a Next-Generation Open Source Framework for Deep LearningCode0
A simple coding for cross-domain matching with dimension reduction via spectral graph embedding—0
Outperforming Word2Vec on Analogy Tasks with Random Projections—0
Rehabilitation of Count-based Models for Word Vector Representations—0
Sequential Labeling with online Deep Learning—0
Web image annotation by diffusion maps manifold learning algorithm—0
Probabilistic low-rank matrix completion on finite alphabets—0
Dimensionality Reduction with Subspace Structure Preservation—0
Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?—0
Subspace Embeddings for the Polynomial Kernel—0
Sparse Variational Bayesian Approximations for Nonlinear Inverse Problems: applications in nonlinear elastography—0
Cone-Constrained Principal Component Analysis—0
Metrics for Probabilistic Geometries—0
Worst-Case Linear Discriminant Analysis as Scalable Semidefinite Feasibility Problems—0
A Convex Sparse PCA for Feature Analysis—0
A Convex Formulation for Spectral Shrunk Clustering—0
Similarity Learning for High-Dimensional Sparse DataCode0
Distributed Low-Rank Estimation Based on Joint Iterative Optimization in Wireless Sensor Networks—0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation—0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
Where do goals come from? A Generic Approach to Autonomous Goal-System Development—0
MKL-RT: Multiple Kernel Learning for Ratio-trace Problems via Convex Optimization—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