2 papers
stat.ML2026
Dataset Pruning from First Principles: A Label-Free Linear Programming Approach
Rodrigo Schuller, Francisco Ganacim
Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically assume that nearby points in e…
math.OC2026
Functional Gradient Descent with Adaptive Representations
Daniel Csillag, Rodrigo Schuller, Pedro Dall'Antonia +3
Functional optimization problems are typically solved by optimizing the parameters of a fixed representation, such as a neural network, resulting in highly nonconvex losses that co…