SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1651–1700 of 3304 papers

TitleStatusHype
Smaller Is Better: An Analysis of Instance Quantity/Quality Trade-off in Rehearsal-based Continual Learning—0
Visualizing Representations of Adversarially Perturbed InputsCode0
An Impossibility Theorem for Node Embedding—0
Investigating Manifold Neighborhood size for Nonlinear Analysis of LIBS Amino Acid Spectra—0
Hierarchical Subspace Learning for Dimensionality Reduction to Improve Classification Accuracy in Large Data Sets—0
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality—0
A Clustering Framework for Residential Electric Demand ProfilesCode0
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data—0
Brain Inspired Face Recognition: A Computational Framework—0
Forensic Analysis of Video Files Using Metadata—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction—0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection ApproachCode0
Contextual Bandits with Sparse Data in Web setting—0
Ovarian Cancer Detection based on Dimensionality Reduction Techniques and Genetic Algorithm—0
Automatic Collection Creation and Recommendation—0
Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombinationCode0
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction NetworksCode0
Multi-view Clustering via Deep Matrix Factorization and Partition Alignment—0
Tensor Random Projection for Low Memory Dimension Reduction—0
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential EquationsCode0
Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data AnalysisCode0
Efficient channel charting via phase-insensitive distance computation—0
Chasing Collective Variables using Autoencoders and biased trajectories—0
On Geodesic Distances and Contextual Embedding Compression for Text ClassificationCode0
Towards Exploratory Landscape Analysis for Large-scale Optimization: A Dimensionality Reduction FrameworkCode0
Compact and Effective Representations for Sketch-based Image Retrieval—0
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopyCode0
Multidimensional Scaling for Gene Sequence Data with Autoencoders—0
Quantum algorithms for SVD-based data representation and analysisCode0
Grassmann Iterative Linear Discriminant Analysis with Proxy Matrix Optimization—0
Capturing patterns of variation unique to a specific datasetCode0
Jointly Modeling and Clustering Tensors in High Dimensions—0
Classifying herbal medicine origins by temporal and spectral data mining of electronic noseCode0
Unsupervised low-rank representations for speech emotion recognition—0
Revisiting Bayesian Autoencoders with MCMCCode0
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap—0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Granger Causality Based Hierarchical Time Series Clustering for State Estimation—0
Class-Wise Principal Component Analysis for hyperspectral image feature extraction—0
Deep Features for training Support Vector Machine—0
Predicting Inflation with Recurrent Neural Networks—0
Adapting Speaker Embeddings for Speaker Diarisation—0
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers—0
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression—0
Deep Learning of Conjugate MappingsCode0
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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