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Supervised dimensionality reduction

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Showing 26–50 of 57 papers

TitleStatusHype
Supervised Dimensionality Reduction via Distance Correlation Maximization—0
Supervised Exponential Family Principal Component Analysis via Convex Optimization—0
Supervised Manifold Learning via Random Forest Geometry-Preserving Proximities—0
Supervised Visualization for Data Exploration—0
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks—0
Yet Another Algorithm for Supervised Principal Component Analysis: Supervised Linear Centroid-Encoder—0
Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction—0
Joint Dimensionality Reduction for Separable Embedding Estimation—0
K-SpecPart: Supervised embedding algorithms and cut overlay for improved hypergraph partitioning—0
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning—0
Learning Low-Dimensional Temporal Representations—0
Local Shrunk Discriminant Analysis (LSDA)—0
Manifold Partition Discriminant Analysis—0
Multiclass spectral feature scaling method for dimensionality reduction—0
Multi-Label Prediction via Sparse Infinite CCA—0
Noisy multi-label semi-supervised dimensionality reduction—0
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis—0
Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings—0
Optimal learning rates for Kernel Conjugate Gradient regression—0
Supervised Dimensionality Reduction for Big DataCode0
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A HumanCode0
Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General RelativityCode0
SRP: Efficient class-aware embedding learning for large-scale data via supervised random projectionsCode0
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution DataCode0
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality ReductionCode0
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