3 papers
stat.ML2026
The MAPS Algorithm: Fast model-agnostic and distribution-free prediction intervals for supervised learning
Daniel Salnikov, Dan Leonte, Kevin Michalewicz
A fundamental problem in modern supervised learning is computing reliable conditional prediction intervals in high-dimensional settings: existing methods often rely on restrictive…
cs.MA2026
Convergence and Connectivity: Dynamics of Multi-Agent Q-Learning in Random Networks
Dan Leonte, Aamal Hussain, Raphael Huser +2
Beyond specific settings, many multi-agent learning algorithms fail to converge to an equilibrium solution, instead displaying complex, non-stationary behaviours such as recurrent…
stat.ML2025
Simulation-based inference via telescoping ratio estimation for trawl processes
Dan Leonte, Raphaël Huser, Almut E. D. Veraart
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussi…