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Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1326–1350 of 3304 papers

TitleStatusHype
Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets—0
Self-Supervised Training with Autoencoders for Visual Anomaly Detection—0
Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion RecognitionCode0
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation ApproachCode0
Regression of high dimensional angular momentum states of light—0
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements—0
Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data—0
Scalable Differentially Private Clustering via Hierarchically Separated Trees—0
DPDR: A novel machine learning method for the Decision Process for Dimensionality Reduction—0
Improved Gaussian-Bernoulli Restricted Boltzmann Machines for UAV-Ground Communication Systems—0
Bayesian Learning of Parameterised Quantum Circuits—0
ARES: Locally Adaptive Reconstruction-based Anomaly ScoringCode0
"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality ReductionCode0
Broadband Beamforming via Linear Embedding—0
FibeRed: Fiberwise Dimensionality Reduction of Topologically Complex Data with Vector BundlesCode0
Hierarchical mixtures of Gaussians for combined dimensionality reduction and clustering—0
Evolutionary Echo State Network: evolving reservoirs in the Fourier space—0
Exploring Predictive States via Cantor Embeddings and Wasserstein Distance—0
CCP: Correlated Clustering and Projection for Dimensionality ReductionCode0
Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional RegressionCode0
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature RepresentationCode0
Click prediction boosting via Bayesian hyperparameter optimization based ensemble learning pipelines—0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—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