Zobrazeno 1 - 10
of 10 276
pro vyhledávání: '"A. Baiocchi"'
Data collection in an IoT environment requires simple and effective communication solutions to address resource constraints, ensure network efficiency, while achieving scalability. Efficiency is evaluated based on the timeliness of collected data (Ag
Externí odkaz:
http://arxiv.org/abs/2409.00277
Randomized experiments are considered the gold standard for estimating causal effects. However, out of the set of possible randomized assignments, some may be likely to produce poor effect estimates and misleading conclusions. Restricted randomizatio
Externí odkaz:
http://arxiv.org/abs/2408.14669
Autor:
Razzaque, A. B. Abdul, Baiocchi, A.
Efficient data collection from a multitude of Internet of Things (IoT) devices is crucial for various applications, yet existing solutions often struggle with minimizing access delay and Age of Information (AoI), especially when managing multiple sim
Externí odkaz:
http://arxiv.org/abs/2407.16378
We study the question of how best to assign an encouragement in a randomized encouragement study. In our setting, units arrive with covariates, receive a nudge toward treatment or control, acquire one of those statuses in a way that need not align wi
Externí odkaz:
http://arxiv.org/abs/2406.05592
Autor:
Baiocchi, Andrea, Razzaque, Asmad
Limitation of the cost of coordination and contention among a large number of nodes calls for grant-free approaches, exploiting physical layer techniques to solve collisions. Successive Interference Cancellation (SIC) is becoming a key building block
Externí odkaz:
http://arxiv.org/abs/2405.12937
Autor:
Scardapane, Simone, Baiocchi, Alessandro, Devoto, Alessio, Marsocci, Valerio, Minervini, Pasquale, Pomponi, Jary
Publikováno v:
Intelligenza Artificiale, vol. Pre-press, pp. 1-16, 2024
This article summarizes principles and ideas from the emerging area of applying \textit{conditional computation} methods to the design of neural networks. In particular, we focus on neural networks that can dynamically activate or de-activate parts o
Externí odkaz:
http://arxiv.org/abs/2403.07965
The recent surge in 3D data acquisition has spurred the development of geometric deep learning models for point cloud processing, boosted by the remarkable success of transformers in natural language processing. While point cloud transformers (PTs) h
Externí odkaz:
http://arxiv.org/abs/2401.14845
Autor:
HELIX Collaboration, Coutu, S., Allison, P. S., Baiocchi, M., Beatty, J. J., Beaufore, L., Calderon, D. H., Castano, A. G., Chen, Y., Green, N., Hanna, D., Jeon, H. B., Klein, S. B., Kunkler, B., Lang, M., Mbarek, R., McBride, K., Mognet, S. I., Musser, J., Nutter, S., OBrien, S., Park, N., Powledge, K. M., Sakai, K., Tabata, M., Tarle, G., Tuttle, J. M., Visser, G., Wakely, S. P., Yu, M.
HELIX is a new NASA-sponsored instrument aimed at measuring the spectra and composition of light cosmic-ray isotopes from hydrogen to neon nuclei, in particular the clock isotopes 10Be (radioactive, with 1.4 Myr lifetime) and 9Be (stable). The latter
Externí odkaz:
http://arxiv.org/abs/2312.06796
Autor:
Paolo Rosa, Afrouz Farhad, Ali Asghar Talebi, Ali Ameri, Daniele Baiocchi, Marek Halada, Ehsan Rakhshani
Publikováno v:
Journal of Insect Biodiversity and Systematics, Vol 10, Iss 4, Pp 827-951 (2024)
In recent years, the research on the Iranian Chrysididae has been extremely prolific, thanks to the efforts of different teams. After the first checklist published by Rosa et al. (2013), more than one hundred taxa of cuckoo wasps have been recorded a
Externí odkaz:
https://doaj.org/article/f65687b3b549495a826c2ba1424a2986
Autor:
Maria Laura De Angelis, Federica Francescangeli, Eleonora Aricò, Paola Verachi, Massimo Zucchetti, Cristina Matteo, Elena Petricci, Emanuela Pilozzi, Isabella Orienti, Alessandra Boe, Adriana Eramo, Rachele Rossi, Tiberio Corati, Daniele Macchia, Anna Maria Pacca, Ann Zeuner, Marta Baiocchi
Publikováno v:
Journal of Experimental & Clinical Cancer Research, Vol 43, Iss 1, Pp 1-20 (2024)
Abstract Background Prevention and treatment of metastatic breast cancer (BC) is an unmet clinical need. The retinoic acid derivative fenretinide (FeR) was previously evaluated in Phase I-III clinical trials but, despite its excellent tolerability an
Externí odkaz:
https://doaj.org/article/5942086ad2e94655b5f65ad924876c24