SOTAVerified

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 2001–2050 of 3304 papers

TitleStatusHype
Extração e Classificação de Características Radiômicas em Gliomas de Baixo Grau para Análise da Codeleção 1p/19q—0
Triplet-Based Wireless Channel Charting: Architecture and Experiments—0
Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation—0
Adversarial Canonical Correlation AnalysisCode0
A cognitive based Intrusion detection system—0
Transformation Based Deep Anomaly Detection in Astronomical Images—0
OSACT4 Shared Task on Offensive Language Detection: Intensive Preprocessing-Based Approach—0
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering—0
Exchangeability, Conformal Prediction, and Rank Tests—0
Solving Large-Scale Sparse PCA to Certifiable (Near) OptimalityCode0
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case StudyCode0
Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction—0
Regularized Pooling—0
Low-Rank Nonlinear Decoding of μ-ECoG from the Primary Auditory Cortex—0
Probing Criticality in Quantum Spin Chains with Neural Networks—0
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization—0
The Information Bottleneck Problem and Its Applications in Machine Learning—0
Memory-efficient training with streaming dimensionality reduction—0
Spectral Learning on Matrices and Tensors—0
Multi-Objective Evolutionary approach for the Performance Improvement of Learners using Ensembling Feature selection and Discretization Technique on Medical data—0
Understanding Aesthetic Evaluation using Deep Learning—0
Beyond Fine-tuning: Few-Sample Sentence Embedding Transfer—0
Estimating a Brain Network Predictive of Stress and Genotype with Supervised AutoencodersCode0
Latent regularization for feature selection using kernel methods in tumor classificationCode0
TensorProjection Layer: A Tensor-Based Dimension Reduction Method in Deep Neural NetworksCode0
Nonlinear Dimensionality Reduction for Data Visualization: An Unsupervised Fuzzy Rule-based Approach—0
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese NetworksCode0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—0
Backprojection for Training Feedforward Neural Networks in the Input and Feature SpacesCode0
DNA Methylation Data to Predict Suicidal and Non-Suicidal Deaths: A Machine Learning Approach—0
Weighted Fisher Discriminant Analysis in the Input and Feature SpacesCode0
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders—0
Company classification using machine learning—0
A new set of cluster driven composite development indicators—0
Gaze-Sensing LEDs for Head Mounted Displays—0
Coupled Control Systems: Periodic Orbit Generation with Application to Quadrupedal Locomotion—0
Unsupervised machine learning of quantum phase transitions using diffusion maps—0
Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters—0
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—0
Multivariate Functional Regression via Nested Reduced-Rank Regularization—0
Multi-Scale Superpatch Matching using Dual Superpixel Descriptors—0
Xtreaming: an incremental multidimensional projection technique and its application to streaming data—0
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks—0
Spherical Principal Curves—0
Graphon Pooling in Graph Neural Networks—0
Fully Convolutional Variational Autoencoder For Feature Extraction Of Fire Detection SystemCode0
Supervised Dimensionality Reduction and Visualization using Centroid-encoder—0
The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization With Adversarial Outliers, and the Recovery—0
High-Dimensional Feature Selection for Genomic DatasetsCode0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
Show:102550
← PrevPage 41 of 67Next →
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