42 citations
- Italian Institute of TechnologyIT11 papers
- University of GenoaIT10 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Massachusetts Institute of TechnologyUS3 papers
- GIPSA-LabFR2 papers
- IMT School for Advanced Studies LuccaIT2 papers
- Limassol General HospitalCY2 papers
- Politecnico di MilanoIT2 papers
- Ubitech (Greece)GR2 papers
- Université Grenoble AlpesFR2 papers
- University of PisaIT2 papers
- Aix-Marseille UniversitéFR1 paper
30 papers
Intuitive Programming, Adaptive Task Planning, and Dynamic Role Allocation in Human-Robot Collaboration
Marta Lagomarsino, Elena Merlo, Andrea Pupa +5
Remarkable capabilities have been achieved by robotics and AI, mastering complex tasks and environments. Yet, humans often remain passive observers, fascinated but uncertain how to…
AI-GenBench: A New Ongoing Benchmark for AI-Generated Image Detection
Lorenzo Pellegrini, Davide Cozzolino, Serafino Pandolfini +5
The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity…
A machine-learning photometric classifier for massive stars in nearby galaxies II. The catalog
G. Maravelias, A. Z. Bonanos, K. Antoniadis +8
Mass loss is a key aspect of stellar evolution, particularly in evolved massive stars, yet episodic mass loss remains poorly understood. To investigate this, we need evolved massiv…
Box-constrained L0 Bregman-relaxations
Mhamed Essafri, Luca Calatroni, Emmanuel Soubies
Regularization using the L0 pseudo-norm is a common approach to promote sparsity, with widespread applications in machine learning and signal processing. However, solving such prob…
A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations
Antoine Chatalic, Marco Letizia, Nicolas Schreuder +1
Two-sample hypothesis testing-determining whether two sets of data are drawn from the same distribution-is a fundamental problem in statistics and machine learning with broad scien…
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé +4
In this paper, we study how the Koopman operator framework can be combined with kernel methods to effectively control nonlinear dynamical systems. While kernel methods have typical…