From the 1 of 3 linked papers with an AI index.
3 papers
stat.ML2026
Survival of the fittest Cox model: Pivotal variable selection for time-to-event data
Maxime van Cutsem, Sylvain Sardy
The paper introduces a pivotal variable selection method for Cox proportional hazards models by applying a square‑root transformation to the partial likelihood, which makes the cho…
math.ST2026
The Pivotal Information Criterion
Sylvain Sardy, Maxime van Cutsem, Sara van de Geer
The Bayesian and Akaike information criteria aim at finding a good balance between under- and over-fitting. They are extensively used every day by practitioners. Yet we contend the…
stat.ML2025
Validation-Free Sparse Learning: A Phase Transition Approach to Feature Selection
Sylvain Sardy, Maxime van Cutsem, Xiaoyu Ma
The growing environmental footprint of artificial intelligence (AI), especially in terms of storage and computation, calls for more frugal and interpretable models. Sparse models (…