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 2151–2200 of 3304 papers

TitleStatusHype
Semantic Relatedness Based Re-ranker for Text SpottingCode0
Knowledge Discovery In Nanophotonics Using Geometric Deep Learning—0
Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecastingCode0
Multi-Perspective, Simultaneous EmbeddingCode0
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion—0
Revealing computational mechanisms of retinal prediction via model reduction—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
A Flexible Framework for Anomaly Detection via Dimensionality ReductionCode0
Imitation Learning from Pixel-Level Demonstrations by HashReward—0
Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation ClassificationCode0
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion—0
Solving Interpretable Kernel Dimension ReductionCode0
Quantized Fisher Discriminant AnalysisCode0
Restricted Minimum Error Entropy Criterion for Robust Classification—0
Fusing Vector Space Models for Domain-Specific Applications—0
Progressive Disentanglement Using Relevant Factor VAE—0
Latent Gaussian process with composite likelihoods and numerical quadrature—0
Lifetime Ruin under High-watermark Fees and Drift Uncertainty—0
Mixture Probabilistic Principal Geodesic Analysis—0
A study of semantic augmentation of word embeddings for extractive summarization—0
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Estimation of a function of low local dimensionality by deep neural networks—0
EEG Signal Dimensionality Reduction and Classification using Tensor Decomposition and Deep Convolutional Neural Networks—0
Principal Component Analysis Using Structural Similarity Index for ImagesCode0
Locally Linear Image Structural Embedding for Image Structure Manifold LearningCode0
Unsupervised Construction of Knowledge Graphs From Text and Code—0
Time series model selection with a meta-learning approach; evidence from a pool of forecasting algorithms—0
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics—0
Locally Linear Embedding and fMRI feature selection in psychiatric classification—0
Tensor-Train Parameterization for Ultra Dimensionality Reduction—0
Null Space Analysis for Class-Specific Discriminant Learning—0
A Critical Note on the Evaluation of Clustering Algorithms—0
Zero-Shot Feature Selection via Transferring Supervised Knowledge—0
GridDehazeNet: Attention-Based Multi-Scale Network for Image DehazingCode0
Improving Channel Charting with Representation-Constrained Autoencoders—0
Visualizing the PHATE of Neural NetworksCode0
Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored ProjectionsCode0
Neuroscience-inspired online unsupervised learning algorithms—0
Likelihood Contribution based Multi-scale Architecture for Generative Flows—0
Effective Dimensionality Reduction for Word EmbeddingsCode0
Machine learning in APOGEE: Identification of stellar populations through chemical abundances—0
Autoencoding with a Learning Classifier System: Initial Results—0
Interpretability Beyond Classification Output: Semantic Bottleneck Networks—0
Completing partial recipes using item-based collaborative filtering to recommend ingredientsCode0
Performance-Complexity Tradeoffs in Greedy Weak Submodular Maximization with Random Sampling—0
Word Sense Disambiguation using Diffusion Kernel PCA—0
High Dimensional Bayesian Optimization via Supervised Dimension ReductionCode0
Compressed Subspace Learning Based on Canonical Angle Preserving Property—0
Multiscale Principle of Relevant Information for Hyperspectral Image ClassificationCode0
The Perfect Marriage and Much More: Combining Dimension Reduction, Distance Measures and Covariance—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