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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 2826–2850 of 3304 papers

TitleStatusHype
Stochastic Multidimensional Scaling—0
Fractal Descriptors of Texture Images Based on the Triangular Prism Dimension—0
High Performance Software in Multidimensional Reduction Methods for Image Processing with Application to Ancient Manuscripts—0
Self-calibrating Neural Networks for Dimensionality Reduction—0
Non-Redundant Spectral Dimensionality Reduction—0
SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives—0
Dimensionality Reduction of Massive Sparse Datasets Using Coresets—0
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity—0
LSTM Autoencoders for Dialect Analysis—0
Large Margin Discriminant Dimensionality Reduction in Prediction Space—0
Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures—0
Image-based localization using LSTMs for structured feature correlation—0
ResFeats: Residual Network Based Features for Image Classification—0
Scalable Adaptive Stochastic Optimization Using Random Projections—0
Firing Rate Dynamics in Recurrent Spiking Neural Networks with Intrinsic and Network Heterogeneity—0
Faster variational inducing input Gaussian process classification—0
Generalized BackPropagation, Étude De Cas: Orthogonality—0
Generalisation and Sharing in Triplet Convnets for Sketch based Visual Search—0
Chiron: A Robust Recommendation System with Graph Regularizer—0
Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction—0
Error Metrics for Learning Reliable Manifolds from Streaming Data—0
Policy Search with High-Dimensional Context Variables—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Information-Theoretic Bounds and Approximations in Neural Population Coding—0
Quantum Laplacian Eigenmap—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