Zobrazeno 1 - 10
of 1 053
pro vyhledávání: '"Gérome, P."'
Autor:
Lee, Man-Yin Leo, Yan, Renbin, Ji, Xihan, Algodon, Gerome, Westfall, Kyle, Lin, Zesen, Belfiore, Francesco, Bundy, Kevin
In non-star-forming, passively evolving galaxies, regions with emission lines dominated by low-ionization species are classified as Low-Ionization Emission Regions (LIERs). The ionization mechanism behind such regions has long been a mystery. Active
Externí odkaz:
http://arxiv.org/abs/2408.07952
Autor:
Feng, Chao, Celdrán, Alberto Huertas, von der Assen, Jan, Beltrán, Enrique Tomás Martínez, Bovet, Gérôme, Stiller, Burkhard
Federated Learning (FL) has emerged as a promising approach to address privacy concerns inherent in Machine Learning (ML) practices. However, conventional FL methods, particularly those following the Centralized FL (CFL) paradigm, utilize a central s
Externí odkaz:
http://arxiv.org/abs/2407.08652
Prompting and Multiple Choices Questions (MCQ) have become the preferred approach to assess the capabilities of Large Language Models (LLMs), due to their ease of manipulation and evaluation. Such experimental appraisals have pointed toward the LLMs'
Externí odkaz:
http://arxiv.org/abs/2406.14986
Autor:
Nanayakkara, Priyanka, Kim, Hyeok, Wu, Yifan, Sarvghad, Ali, Mahyar, Narges, Miklau, Gerome, Hullman, Jessica
Publikováno v:
in 2024 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA, 2024 pp. 231-231
Differential privacy (DP) has the potential to enable privacy-preserving analysis on sensitive data, but requires analysts to judiciously spend a limited ``privacy loss budget'' $\epsilon$ across queries. Analysts conducting exploratory analyses do n
Externí odkaz:
http://arxiv.org/abs/2406.01964
Diffusion models recently proved to be remarkable priors for Bayesian inverse problems. However, training these models typically requires access to large amounts of clean data, which could prove difficult in some settings. In this work, we present a
Externí odkaz:
http://arxiv.org/abs/2405.13712
Autor:
Sánchez, Pedro Miguel Sánchez, Celdrán, Alberto Huertas, Bovet, Gérôme, Pérez, Gregorio Martínez
In the current cybersecurity landscape, protecting military devices such as communication and battlefield management systems against sophisticated cyber attacks is crucial. Malware exploits vulnerabilities through stealth methods, often evading tradi
Externí odkaz:
http://arxiv.org/abs/2405.09318
Autor:
da Silva, Ricardo E., Osório, Jonas H., Webb, David J., Gérôme, Frédéric, Benabid, Fetah, Franco, Marcos A. R., Cordeiro, Cristiano M. B.
We demonstrate the acousto-optic modulation of a hybrid-lattice hollow core fiber (HL-HCF) for the first time. For many years, optical fibers with reduced diameters have been the main solution to increase the interaction of acoustic and optical waves
Externí odkaz:
http://arxiv.org/abs/2405.01779
Mechanisms for generating differentially private synthetic data based on marginals and graphical models have been successful in a wide range of settings. However, one limitation of these methods is their inability to incorporate public data. Initiali
Externí odkaz:
http://arxiv.org/abs/2403.07797
Autor:
von der Assen, Jan, Sharif, Jamo, Feng, Chao, Killer, Christian, Bovet, Gérôme, Stiller, Burkhard
Threat modeling is a popular method to securely develop systems by achieving awareness of potential areas of future damage caused by adversaries. However, threat modeling for systems relying on Artificial Intelligence is still not well explored. Whil
Externí odkaz:
http://arxiv.org/abs/2403.06512
Autor:
da Silva, Ricardo E., Osório, Jonas H., Rodrigues, Gabriel L., Webb, David J., Gérôme, Frédéric, Benabid, Fetah, Cordeiro, Cristiano M. B., Franco, Marcos A. R.
The modulation efficiency of a tubular-lattice hollow-core fiber (HCF) by means of flexural acoustic waves is investigated in detail for the first time. The main acousto-optic properties of the HCF are evaluated employing 2D and 3D models based on th
Externí odkaz:
http://arxiv.org/abs/2402.15825