SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1951–2000 of 3304 papers

TitleStatusHype
Semi-supervised Embedding Learning for High-dimensional Bayesian OptimizationCode0
QEBA: Query-Efficient Boundary-Based Blackbox Attack—0
Physically interpretable machine learning algorithm on multidimensional non-linear fields—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
Extração e Classificação de Características Radiômicas em Gliomas de Baixo Grau para Análise da Codeleção 1p/19q—0
Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks—0
Triplet-Based Wireless Channel Charting: Architecture and Experiments—0
DartMinHash: Fast Sketching for Weighted SetsCode1
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
Detection and Retrieval of Out-of-Distribution Objects in Semantic SegmentationCode1
OSACT4 Shared Task on Offensive Language Detection: Intensive Preprocessing-Based Approach—0
Exchangeability, Conformal Prediction, and Rank Tests—0
Fast Network Embedding Enhancement via High Order Proximity ApproximationCode1
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering—0
Solving Large-Scale Sparse PCA to Certifiable (Near) OptimalityCode0
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case StudyCode0
Low-Rank Nonlinear Decoding of μ-ECoG from the Primary Auditory Cortex—0
Regularized Pooling—0
Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction—0
Probing Criticality in Quantum Spin Chains with Neural Networks—0
Renormalized Mutual Information for Artificial Scientific DiscoveryCode1
On time series representations for multi-label NILMCode1
Sign Bits Are All You Need for Black-Box AttacksCode1
BayesOpt Adversarial AttackCode1
The Information Bottleneck Problem and Its Applications in Machine Learning—0
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization—0
Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!Code1
Memory-efficient training with streaming dimensionality reduction—0
ivis Dimensionality Reduction Framework for Biomacromolecular SimulationsCode3
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
Latent regularization for feature selection using kernel methods in tumor classificationCode0
Beyond Fine-tuning: Few-Sample Sentence Embedding Transfer—0
Estimating a Brain Network Predictive of Stress and Genotype with Supervised AutoencodersCode0
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
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
Backprojection for Training Feedforward Neural Networks in the Input and Feature SpacesCode0
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese NetworksCode0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—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
DNA Methylation Data to Predict Suicidal and Non-Suicidal Deaths: A Machine Learning Approach—0
Company classification using machine learning—0
Flows for simultaneous manifold learning and density estimationCode1
A new set of cluster driven composite development indicators—0
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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