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Dimensionality Reduction

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

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Papers

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Showing 851–900 of 3304 papers

TitleStatusHype
Detecting the Trend in Musical Taste over the Decade -- A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features—0
Detection and Evaluation of Clusters within Sequential Data—0
Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery—0
Classification of high-dimensional data with spiked covariance matrix structure—0
Detection and tracking of gas plumes in LWIR hyperspectral video sequence data—0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
DG-GL: Differential geometry based geometric learning of molecular datasets—0
Diagnosing ADHD from fMRI Scans Using Hidden Markov Models—0
Classification of EEG Signals using Genetic Programming for Feature Construction—0
Diagnosis of Patients with Viral, Bacterial, and Non-Pneumonia Based on Chest X-Ray Images Using Convolutional Neural Networks—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
A framework for streamlined statistical prediction using topic models—0
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization—0
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
Classification of Cervical Cancer Dataset—0
Diffeomorphic Dimensionality Reduction—0
Attention or memory? Neurointerpretable agents in space and time—0
Differentially private sliced inverse regression in the federated paradigm—0
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm—0
Differential Privacy for Clustering Under Continual Observation—0
Classification Methods Based on Machine Learning for the Analysis of Fetal Health Data—0
Difficulty in estimating visual information from randomly sampled images—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks—0
Diffusion Fingerprints—0
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis—0
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—0
Diffusion Maps : Using the Semigroup Property for Parameter Tuning—0
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks—0
Digital Fingerprinting of Microstructures—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—0
DimenFix: A novel meta-dimensionality reduction method for feature preservation—0
Dimensionality-reduced subspace clustering—0
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder—0
A Unified Framework for Optimization-Based Graph Coarsening—0
Dimensionality Reduction and Classification feature using Mutual Information applied to Hyperspectral Images : A Filter strategy based algorithm—0
Classic machine learning methods—0
Dimensionality reduction, and function approximation of poly(lactic-co-glycolic acid) micro- and nanoparticle dissolution rate—0
Dimensionality Reduction and Motion Clustering during Activities of Daily Living: 3, 4, and 7 Degree-of-Freedom Arm Movements—0
Dimensionality Reduction and Prioritized Exploration for Policy Search—0
Dimensionality Reduction and State Space Systems: Forecasting the US Treasury Yields Using Frequentist and Bayesian VARs—0
Dimensionality Reduction and Wasserstein Stability for Kernel Regression—0
Dimensionality Reduction as Probabilistic Inference—0
Dimensionality reduction based on Distance Preservation to Local Mean (DPLM) for SPD matrices and its application in BCI—0
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification—0
Dimensionality Reduction Ensembles—0
Likelihood Contribution based Multi-scale Architecture for Generative Flows—0
An Impossibility Theorem for Node Embedding—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