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Supervised dimensionality reduction
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논문
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A Convex formulation for linear discriminant analysis
Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality Reduction
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data
An Embedding is Worth a Thousand Noisy Labels
Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension
Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction
Curvature Augmented Manifold Embedding and Learning
Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
Supervised Manifold Learning via Random Forest Geometry-Preserving Proximities
Yet Another Algorithm for Supervised Principal Component Analysis: Supervised Linear Centroid-Encoder
K-SpecPart: Supervised embedding algorithms and cut overlay for improved hypergraph partitioning
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis
Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General Relativity
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A Human
Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks
SLISEMAP: Supervised dimensionality reduction through local explanations
Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication
Scalable semi-supervised dimensionality reduction with GPU-accelerated EmbedSOM
Computer-aided Interpretable Features for Leaf Image Classification
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks
Joint Dimensionality Reduction for Separable Embedding Estimation
Entangled Kernels -- Beyond Separability
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction
Manifold Partition Discriminant Analysis
Supervised dimensionality reduction by a Linear Discriminant Analysis on pre-trained CNN features
Supervised Visualization for Data Exploration
Supervised Dimensionality Reduction and Visualization using Centroid-encoder
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction
Multiclass spectral feature scaling method for dimensionality reduction
Adapting Text Embeddings for Causal Inference
Noisy multi-label semi-supervised dimensionality reduction
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach
SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections
Spectral feature scaling method for supervised dimensionality reduction
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