Zobrazeno 1 - 10
of 12 394
pro vyhledávání: '"P Marchi"'
Shapley values have seen widespread use in machine learning as a way to explain model predictions and estimate the importance of covariates. Accurately explaining models is critical in real-world models to both aid in decision making and to infer the
Externí odkaz:
http://arxiv.org/abs/2408.08845
Quasi-stationary Mean Field Games models consider agents who base their strategies on current information without forecasting future states. In this paper we address the first-order quasi-stationary Mean Field Games system, which involves an ergodic
Externí odkaz:
http://arxiv.org/abs/2409.18483
Autor:
Bandiziol, Cinzia, De Marchi, Stefano
The aim of the present work is a comparative study of different persistence kernels applied to various classification problems. After some necessary preliminaries on homology and persistence diagrams, we introduce five different kernels that are then
Externí odkaz:
http://arxiv.org/abs/2408.07090
Autor:
Levison, Harold F., Marchi, Simone, Noll, Keith S., Spencer, John R., Statler, Thomas S., team, the Lucy mission
Asteroids with diameters less than about 5 km have complex histories because they are small enough for radiative torques, YORP, to be a notable factor in their evolution. (152830) Dinkinesh is a small asteroid orbiting the Sun near the inner edge of
Externí odkaz:
http://arxiv.org/abs/2406.19337
Autor:
De Marchi, Alberto
Necessary optimality conditions in Lagrangian form and the augmented Lagrangian framework are extended to mixed-integer nonlinear optimization, without any convexity assumptions. Building upon a recently developed notion of local optimality for probl
Externí odkaz:
http://arxiv.org/abs/2406.12436
Autor:
De Marchi, Alberto, Themelis, Andreas
Focusing on minimization problems with structured objective function and smooth constraints, we present a flexible technique that combines the beneficial regularization effects of (exact) penalty and interior-point methods. Working in the fully nonco
Externí odkaz:
http://arxiv.org/abs/2406.09901
Autor:
Occhipinti, Daniela, Marchi, Michele, Mondella, Irene, Lai, Huiyuan, Dell'Orletta, Felice, Nissim, Malvina, Guerini, Marco
Automatic methods for generating and gathering linguistic data have proven effective for fine-tuning Language Models (LMs) in languages less resourced than English. Still, while there has been emphasis on data quantity, less attention has been given
Externí odkaz:
http://arxiv.org/abs/2406.07288
We provide a representation of the weak solution of the continuity equation on the Heisenberg group $\mathbb H^1$ with periodic data (the periodicity is suitably adapted to the group law). This solution is the push forward of a measure concentrated o
Externí odkaz:
http://arxiv.org/abs/2406.02145
We tackle the question of whether Large Language Models (LLMs), viewed as dynamical systems with state evolving in the embedding space of symbolic tokens, are observable. That is, whether there exist multiple 'mental' state trajectories that yield th
Externí odkaz:
http://arxiv.org/abs/2405.14061
Publikováno v:
A&A 688, A111 (2024)
Context. A necessary ingredient in understanding the star formation history of a young cluster is knowledge of the extinction towards the region. This has typically been done by making use of the colour-difference method with photometry, or similar m
Externí odkaz:
http://arxiv.org/abs/2405.08445