SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3101–3150 of 3304 papers

TitleStatusHype
Supervised dimensionality reduction by a Linear Discriminant Analysis on pre-trained CNN featuresCode0
CatBoost: unbiased boosting with categorical featuresCode0
Capturing patterns of variation unique to a specific datasetCode0
On genetic programming representations and fitness functions for interpretable dimensionality reductionCode0
On Geodesic Distances and Contextual Embedding Compression for Text ClassificationCode0
Weighted Fisher Discriminant Analysis in the Input and Feature SpacesCode0
Capacity Preserving Mapping for High-dimensional Data VisualizationCode0
Sirius: Visualization of Mixed Features as a Mutual Information Network GraphCode0
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality ReductionCode0
Online Convex Matrix Factorization with Representative RegionsCode0
Lens functions for exploring UMAP Projections with Domain KnowledgeCode0
Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored ProjectionsCode0
Calibrating dimension reduction hyperparameters in the presence of noiseCode0
Data Mapping and Finite Difference LearningCode0
From deep learning to mechanistic understanding in neuroscience: the structure of retinal predictionCode0
From Gameplay to Symbolic Reasoning: Learning SAT Solver Heuristics in the Style of Alpha(Go) ZeroCode0
From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain AdaptationCode0
LEt-SNE: A Hybrid Approach To Data Embedding and Visualization of Hyperspectral ImageryCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
A journey in ESN and LSTM visualisations on a language taskCode0
From Principal Subspaces to Principal Components with Linear AutoencodersCode0
Visualizing the PHATE of Neural NetworksCode0
From Small to Large Language Models: Revisiting the Federalist PapersCode0
Caffe: Convolutional Architecture for Fast Feature EmbeddingCode0
Recommending research articles to consumers of online vaccination informationCode0
Sketching out the Details: Sketch-based Image Retrieval using Convolutional Neural Networks with Multi-stage RegressionCode0
Fully Convolutional Variational Autoencoder For Feature Extraction Of Fire Detection SystemCode0
ALPCAHUS: Subspace Clustering for Heteroscedastic DataCode0
Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in ConnectomicsCode0
Functional Diffusion MapsCode0
Leveraging Unsupervised Image Registration for Discovery of Landmark Shape DescriptorCode0
Online Recognition of Incomplete Gesture Data to Interface Collaborative RobotsCode0
ALPCAH: Subspace Learning for Sample-wise Heteroscedastic DataCode0
Function Preserving Projection for Scalable Exploration of High-Dimensional DataCode0
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components AnalysisCode0
Funnels: Exact maximum likelihood with dimensionality reductionCode0
Fun with Flags: Robust Principal Directions via Flag ManifoldsCode0
A novel approach for Fair Principal Component Analysis based on eigendecompositionCode0
On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical PhenomenaCode0
Bubblewrap: Online tiling and real-time flow prediction on neural manifoldsCode0
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signalsCode0
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern DataCode0
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value RegularizationCode0
Game-theoretic Objective Space PlanningCode0
An Information Theory-Based Feature Selection Framework for Big Data Under Apache SparkCode0
On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problemsCode0
Asymptotics for Sketching in Least Squares RegressionCode0
On Projections to Linear SubspacesCode0
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components AnalysisCode0
Linear Dimensionality Reduction: Survey, Insights, and GeneralizationsCode0
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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