6 papers
Non-smooth stochastic gradient descent using smoothing functions
Tommaso Giovannelli, Jingfu Tan, Luis Nunes Vicente
In this paper, we address stochastic optimization problems involving a composition of a non-smooth outer function and a smooth inner function, a formulation frequently encountered…
CHAL: Council of Hierarchical Agentic Language
Tommaso Giovannelli, Griffin D. Kent
Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structural limitations: debate tend…
Pareto sensitivity, most-changing sub-fronts, and knee solutions
Tommaso Giovannelli, Marcos Medeiros Raimundo, Luis Nunes Vicente
When dealing with a multi-objective optimization problem, obtaining a comprehensive representation of the set of Pareto optimal solutions can be computationally expensive. However,…
Stochastic set-valued optimization and its application to robust learning
Tommaso Giovannelli, Jingfu Tan, Luis Nunes Vicente
In this paper, we develop a stochastic set-valued optimization (SVO) framework tailored for robust machine learning. In the SVO setting, each decision variable is mapped to a set o…
Comparison of derivative-free and gradient-based minimization for multi-objective compositional design of shape memory alloys
S. Josyula, Y. Noiman, E. J. Payton +1
Designing shape memory alloys (SMAs) that meet performance targets while remaining affordable and sustainable is a complex challenge. In this work, we focus on optimizing SMA compo…
A stochastic gradient method for trilevel optimization
Tommaso Giovannelli, Griffin Dean Kent, Luis Nunes Vicente
With the success that the field of bilevel optimization has seen in recent years, similar methodologies have started being applied to solving more difficult applications that arise…