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 251–300 of 3304 papers

TitleStatusHype
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—0
A Discussion On the Validity of Manifold Learning—0
Exact Cluster Recovery via Classical Multidimensional Scaling—0
An Analysis of the t-SNE Algorithm for Data Visualization—0
A clustering adaptive Gaussian process regression method: response patterns based real-time prediction for nonlinear solid mechanics problems—0
Approaching Metaheuristic Deep Learning Combos for Automated Data Mining—0
Approximated and User Steerable tSNE for Progressive Visual Analytics—0
Approximation of Functions over Manifolds: A Moving Least-Squares Approach—0
An Algorithm and Heuristic based on Normalized Mutual Information for Dimensionality Reduction and Classification of Hyperspectral images—0
A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution—0
A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering—0
An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization—0
A Deep Signed Directional Distance Function for Object Shape Representation—0
Automated Classification of Dry Bean Varieties Using XGBoost and SVM Models—0
ELBD: Efficient score algorithm for feature selection on latent variables of VAE—0
An adaptive block based integrated LDP,GLCM,and Morphological features for Face Recognition—0
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation—0
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification—0
A Music Classification Model based on Metric Learning and Feature Extraction from MP3 Audio Files—0
A deep-learning based native-language classification by using a latent semantic analysis for the NLI Shared Task 2017—0
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
Applying Ricci Flow to High Dimensional Manifold Learning—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
A Class-Based Agreement Model for Generating Accurately Inflected Translations—0
A Multimodal Intermediate Fusion Network with Manifold Learning for Stress Detection—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
Applying a random projection algorithm to optimize machine learning model for breast lesion classification—0
A Multimodal Data-driven Framework for Anxiety Screening—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
A Deep Graph Embedding Network Model for Face Recognition—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Achieving Fair PCA Using Joint Eigenvalue Decomposition—0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
Applying Graph-based Keyword Extraction to Document Retrieval—0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
A Deep Convolutional Auto-Encoder with Pooling - Unpooling Layers in Caffe—0
Application of Symmetric Uncertainty and Mutual Information to Dimensionality Reduction and Classification of Hyperspectral Images—0
3D Face Recognition with Sparse Spherical Representations—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension—0
Application Research On Real-Time Perception Of Device Performance Status—0
A Method for Classifying Snow Using Ski-Mounted Strain Sensors—0
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction—0
Additive Component Analysis—0
A mechanism-driven reinforcement learning framework for shape optimization of airfoils—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