PCA

3 stories

Stories

Learning to Select Features with Manifold Deep Unfolding PCA
Unsupervised feature selection (UFS) is of great significance in image processing and pattern recognition. Nevertheless, existing model-based methods often rely on manually tuned hyperparameters, while deep learning-based methods generally require massive training data.
arXiv - cs.CV (CV)Oct 15, 20262 min read
PCAsplat: Gaussian Splatting with Local PCA Regularization
Gaussian splatting has emerged as a flexible representation for 3D reconstruction from posed images. However, existing methods are optimized primarily using rasterization-based losses, which supervise a splat only when it contributes to sampled camera rays.
arXiv - cs.CV (CV)Oct 9, 20262 min read
Autoencoders vs. PCA: I Rigged the Test and PCA Still Won
A theoretical advantage that didn't survive contact with a real benchmark. The post Autoencoders vs. PCA: I Rigged the Test and PCA Still Won appeared first on Towards Data Science.
Towards Data ScienceOct 1, 20268 min read

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