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 1051–1100 of 3304 papers

TitleStatusHype
A New Method for Performance Analysis in Nonlinear Dimensionality Reduction—0
A new method color MS-BSIF Features learning for the robust kinship verification—0
Causal learning with sufficient statistics: an information bottleneck approach—0
A feature construction framework based on outlier detection and discriminative pattern mining—0
Enhanced Sampling with Machine Learning: A Review—0
Causal Feature Selection with Dimension Reduction for Interpretable Text Classification—0
Causal Deep Learning—0
A new filter for dimensionality reduction and classification of hyperspectral images using GLCM features and mutual information—0
A New Dimensionality Reduction Method Based on Hensel's Compression for Privacy Protection in Federated Learning—0
A Comparison of Representation Learning Methods for Dimensionality Reduction of fMRI Scans for Classification of ADHD—0
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction—0
CASS: Cross Adversarial Source Separation via Autoencoder—0
A New Covariance Estimator for Sufficient Dimension Reduction in High-Dimensional and Undersized Sample Problems—0
CASE -- Condition-Aware Sentence Embeddings for Conditional Semantic Textual Similarity Measurement—0
Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning—0
A fast, universal algorithm to learn parametric nonlinear embeddings—0
Cardiomyopathy Diagnosis Model from Endomyocardial Biopsy Specimens: Appropriate Feature Space and Class Boundary in Small Sample Size Data—0
Capturing Regional Variation with Distributed Place Representations and Geographic Retrofitting—0
A new band selection approach based on information theory and support vector machine for hyperspectral images reduction and classification—0
A New Approach to Dimensionality Reduction for Anomaly Detection in Data Traffic—0
Capture Agent Free Biosensing using Porous Silicon Arrays and Machine Learning—0
A Second-Order Majorant Algorithm for Nonnegative Matrix Factorization—0
A Comparison of Neural Network Training Methods for Text Classification—0
On Probabilistic Embeddings in Optimal Dimension Reduction—0
Enhancing Few-shot Keyword Spotting Performance through Pre-Trained Self-supervised Speech Models—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
A New Approach for Scalable Analysis of Microbial Communities—0
A comparison of latent semantic analysis and correspondence analysis of document-term matrices—0
Capacity Analysis of Vector Symbolic Architectures—0
Can the Problem-Solving Benefits of Quality Diversity Be Obtained Without Explicit Diversity Maintenance?—0
A Faster Approach to Spiking Deep Convolutional Neural Networks—0
Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical Processes—0
Canonical Variates in Wasserstein Metric Space—0
Canonical Correlation Analysis of Datasets with a Common Source Graph—0
A Neural Operator-Based Emulator for Regional Shallow Water Dynamics—0
Can Genetic Programming Do Manifold Learning Too?—0
CAMEL: Curvature-Augmented Manifold Embedding and Learning—0
A Neural Network Transformer Model for Composite Microstructure Homogenization—0
AEkNN: An AutoEncoder kNN-based classifier with built-in dimensionality reduction—0
A dynamical systems based framework for dimension reduction—0
Efficient Sketching Algorithm for Sparse Binary Data—0
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
Emulators for stellar profiles in binary population modeling—0
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching—0
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION—0
Building Models for Biopathway Dynamics Using Intrinsic Dimensionality Analysis—0
Efficient Optimization for Discriminative Latent Class Models—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX)—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