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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1451–1500 of 3304 papers

TitleStatusHype
Concept Drift Detection in Federated Networked Systems—0
Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons—0
On the use of Wasserstein metric in topological clustering of distributional data—0
Quality-Diversity Meta-Evolution: customising behaviour spaces to a meta-objectiveCode0
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
Ligand-induced protein dynamics differences correlate with protein-ligand binding affinities: An unsupervised deep learning approach—0
An Empirical Study on the Joint Impact of Feature Selection and Data Re-sampling on Imbalance Classification—0
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations—0
Bubblewrap: Online tiling and real-time flow prediction on neural manifoldsCode0
Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN)Code1
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures—0
Convolutional Autoencoders for Reduced-Order Modeling—0
FAST-PCA: A Fast and Exact Algorithm for Distributed Principal Component Analysis—0
Variational embedding of protein folding simulations using gaussian mixture variational autoencoders—0
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial—0
Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey—0
Multi-Criteria Radio Spectrum Sharing With Subspace-Based Pareto Tracing—0
Joint Characterization of Spatiotemporal Data Manifolds—0
Transformers predicting the future. Applying attention in next-frame and time series forecastingCode0
M-ar-K-Fast Independent Component AnalysisCode0
Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI—0
Dimensionality Reduction and State Space Systems: Forecasting the US Treasury Yields Using Frequentist and Bayesian VARs—0
Clustering with UMAP: Why and How Connectivity MattersCode1
Predicting Molecular Phenotypes with Single Cell RNA Sequencing Data: an Assessment of Unsupervised Machine Learning Models—0
ABC-FL: Anomalous and Benign client Classification in Federated Learning—0
Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey—0
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsCode0
A Hybrid Learning Approach to Detecting Regime Switches in Financial Markets—0
High dimensional Bayesian Optimization Algorithm for Complex System in Time Series—0
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
An iterative coordinate descent algorithm to compute sparse low-rank approximations—0
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis SystemsCode0
Machine Learning and Factor-Based Portfolio Optimization—0
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey—0
Preliminary Steps Towards Federated Sentiment Classification—0
A comparison of latent semantic analysis and correspondence analysis of document-term matrices—0
A Deep Signed Directional Distance Function for Object Shape Representation—0
A local approach to parameter space reduction for regression and classification tasksCode1
Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI—0
Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty QuantificationCode0
Manifold learning-based polynomial chaos expansions for high-dimensional surrogate modelsCode1
Machine learning for assessing quality of service in the hospitality sector based on customer reviews—0
Measuring inter-cluster similarities with Alpha Shape TRIangulation in loCal Subspaces (ASTRICS) facilitates visualization and clustering of high-dimensional data—0
Optimality of the Johnson-Lindenstrauss Dimensionality Reduction for Practical Measures—0
Identifying Layers Susceptible to Adversarial Attacks—0
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid SimulationsCode1
On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit—0
WeightScale: Interpreting Weight Change in Neural Networks—0
Generative locally linear embedding: A module for manifold unfolding and visualizationCode1
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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