Zobrazeno 1 - 10
of 18 441
pro vyhledávání: '"Simonetto, A AS"'
Autor:
Rahman, Muhammad Rameez ur, Simonetto, Piero, Polato, Anna, Pasti, Francesco, Tonin, Luca, Vascon, Sebastiano
Open vocabulary 3D object detection (OV3D) allows precise and extensible object recognition crucial for adapting to diverse environments encountered in assistive robotics. This paper presents OpenNav, a zero-shot 3D object detection pipeline based on
Externí odkaz:
http://arxiv.org/abs/2408.13936
While adversarial robustness in computer vision is a mature research field, fewer researchers have tackled the evasion attacks against tabular deep learning, and even fewer investigated robustification mechanisms and reliable defenses. We hypothesize
Externí odkaz:
http://arxiv.org/abs/2408.07579
Autor:
Biwole, A. Tema, Porte, L., Fasoli, A., Figini, L., Decker, J., Hoppe, M., Cazabonne, J., Votta, L., Simonetto, A., Coda, S., Team, TCV
This paper describes the first Vertical Electron Cyclotron Emission (V-ECE) measurement of non-thermal electron distributions in the \textit{Tokamak \`a Configuration Variable}, TCV. These measurements were conducted in runaway electron scenarios and
Externí odkaz:
http://arxiv.org/abs/2407.18780
State-of-the-art deep learning models for tabular data have recently achieved acceptable performance to be deployed in industrial settings. However, the robustness of these models remains scarcely explored. Contrary to computer vision, there are no e
Externí odkaz:
http://arxiv.org/abs/2406.00775
Unitary and non-unitary diagonal operators are fundamental building blocks in quantum algorithms with applications in the resolution of partial differential equations, Hamiltonian simulations, the loading of classical data on quantum computers (quant
Externí odkaz:
http://arxiv.org/abs/2404.02819
The acquisition of objects outside the Line-of-Sight of cameras is a very intriguing but also extremely challenging research topic. Recent works showed the feasibility of this idea exploiting transient imaging data produced by custom direct Time of F
Externí odkaz:
http://arxiv.org/abs/2403.19376
Effective collaboration among heterogeneous clients in a decentralized setting is a rather unexplored avenue in the literature. To structurally address this, we introduce Model Agnostic Peer-to-peer Learning (coined as MAPL) a novel approach to simul
Externí odkaz:
http://arxiv.org/abs/2403.19792
Autor:
Simonetto, Andrea
Can we allow humans to pick among different, yet reasonably similar, decisions? Are we able to construct optimization problems whose outcome are sets of feasible, close-to-optimal decisions for human users to pick from, instead of a single, hardly ex
Externí odkaz:
http://arxiv.org/abs/2403.03847
Autor:
Mauduit, Eliabelle, Simonetto, Andrea
Motivated by extracting and summarizing relevant information in short sentence settings, such as satisfaction questionnaires, hotel reviews, and X/Twitter, we study the problem of clustering words in a hierarchical fashion. In particular, we focus on
Externí odkaz:
http://arxiv.org/abs/2312.04209
State-of-the-art deep learning models for tabular data have recently achieved acceptable performance to be deployed in industrial settings. However, the robustness of these models remains scarcely explored. Contrary to computer vision, there is to da
Externí odkaz:
http://arxiv.org/abs/2311.04503