SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1151–1175 of 3304 papers

TitleStatusHype
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
Principal Geodesic Analysis of Merge Trees (and Persistence Diagrams)—0
Deep Sufficient Representation Learning via Mutual Information—0
CausNet : Generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraintsCode0
Natural language processing for clusterization of genes according to their functions—0
Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation—0
Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions—0
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction—0
On the Selection of Tuning Parameters for Patch-Stitching Embedding Methods—0
Beam-Space MIMO Radar for Joint Communication and Sensing with OTFS Modulation—0
Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution RegressionCode0
Horizontal and Vertical Attention in Transformers—0
Stacked Autoencoder Based Multi-Omics Data Integration for Cancer Survival PredictionCode0
Towards a More Rigorous Science of Blindspot Discovery in Image Classification ModelsCode1
UDRN: Unified Dimensional Reduction Neural Network for Feature Selection and Feature Projection—0
Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data—0
A Hybrid Approach for Binary Classification of Imbalanced Data—0
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs—0
UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes—0
Local manifold learning and its link to domain-based physics knowledgeCode0
Extreme compression of sentence-transformer ranker models: faster inference, longer battery life, and less storage on edge devices—0
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns—0
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition PathsCode1
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
Self-Supervised Training with Autoencoders for Visual Anomaly Detection—0
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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