3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Sparse Linear Centroid-Encoder: A Convex Method for Feature Selection
Tomojit Ghosh, Michael Kirby, Karim Karimov
We present a novel feature selection technique, Sparse Linear Centroid-Encoder (SLCE). The algorithm uses a linear transformation to reconstruct a point as its class centroid and,…
cs.LG2023★ 3 cited
Feature Selection using Sparse Adaptive Bottleneck Centroid-Encoder
Tomojit Ghosh, Michael Kirby
We introduce a novel nonlinear model, Sparse Adaptive Bottleneck Centroid-Encoder (SABCE), for determining the features that discriminate between two or more classes. The algorithm…
cs.LG2023
Yet Another Algorithm for Supervised Principal Component Analysis: Supervised Linear Centroid-Encoder
Tomojit Ghosh, Michael Kirby
We propose a new supervised dimensionality reduction technique called Supervised Linear Centroid-Encoder (SLCE), a linear counterpart of the nonlinear Centroid-Encoder (CE) \citep{…