Zobrazeno 1 - 10
of 16 297
pro vyhledávání: '"Gala, A."'
Autor:
Romero-Tapiador, Sergio, Tolosana, Ruben, Morales, Aythami, Lacruz-Pleguezuelos, Blanca, Pastor, Sofia Bosch, Marcos-Zambrano, Laura Judith, Bazán, Guadalupe X., Freixer, Gala, Vera-Rodriguez, Ruben, Fierrez, Julian, Ortega-Garcia, Javier, Espinosa-Salinas, Isabel, Pau, Enrique Carrillo de Santa
Early detection of chronic and Non-Communicable Diseases (NCDs) is crucial for effective treatment during the initial stages. This study explores the application of wearable devices and Artificial Intelligence (AI) in order to predict weight loss cha
Externí odkaz:
http://arxiv.org/abs/2409.08700
Autor:
Loconte, Lorenzo, Mari, Antonio, Gala, Gennaro, Peharz, Robert, de Campos, Cassio, Quaeghebeur, Erik, Vessio, Gennaro, Vergari, Antonio
This paper establishes a rigorous connection between circuit representations and tensor factorizations, two seemingly distinct yet fundamentally related areas. By connecting these fields, we highlight a series of opportunities that can benefit both c
Externí odkaz:
http://arxiv.org/abs/2409.07953
Autor:
Gala, Gautam, Unte, Tilmann, Maia, Luiz, Kühbacher, Johannes, Kadusale, Isser, Alkoudsi, Mohammad Ibrahim, Fohler, Gerhard, Altmeyer, Sebastian
Publikováno v:
3rd International Workshop on Real-Time Cloud systems (RT-Cloud), held in conjunction with the 36th Euromicro Conference on Real-time Systems (ECRTS) 2024
Edge computing processes data near its source, reducing latency and enhancing security compared to traditional cloud computing while providing its benefits. This paper explores edge computing for migrating an existing safety-critical robotics use cas
Externí odkaz:
http://arxiv.org/abs/2406.14391
Probabilistic integral circuits (PICs) have been recently introduced as probabilistic models enjoying the key ingredient behind expressive generative models: continuous latent variables (LVs). PICs are symbolic computational graphs defining continuou
Externí odkaz:
http://arxiv.org/abs/2406.06494
Autor:
Romero, David, Lyu, Chenyang, Wibowo, Haryo Akbarianto, Lynn, Teresa, Hamed, Injy, Kishore, Aditya Nanda, Mandal, Aishik, Dragonetti, Alina, Abzaliev, Artem, Tonja, Atnafu Lambebo, Balcha, Bontu Fufa, Whitehouse, Chenxi, Salamea, Christian, Velasco, Dan John, Adelani, David Ifeoluwa, Meur, David Le, Villa-Cueva, Emilio, Koto, Fajri, Farooqui, Fauzan, Belcavello, Frederico, Batnasan, Ganzorig, Vallejo, Gisela, Caulfield, Grainne, Ivetta, Guido, Song, Haiyue, Ademtew, Henok Biadglign, Maina, Hernán, Lovenia, Holy, Azime, Israel Abebe, Cruz, Jan Christian Blaise, Gala, Jay, Geng, Jiahui, Ortiz-Barajas, Jesus-German, Baek, Jinheon, Dunstan, Jocelyn, Alemany, Laura Alonso, Nagasinghe, Kumaranage Ravindu Yasas, Benotti, Luciana, D'Haro, Luis Fernando, Viridiano, Marcelo, Estecha-Garitagoitia, Marcos, Cabrera, Maria Camila Buitrago, Rodríguez-Cantelar, Mario, Jouitteau, Mélanie, Mihaylov, Mihail, Imam, Mohamed Fazli Mohamed, Adilazuarda, Muhammad Farid, Gochoo, Munkhjargal, Otgonbold, Munkh-Erdene, Etori, Naome, Niyomugisha, Olivier, Silva, Paula Mónica, Chitale, Pranjal, Dabre, Raj, Chevi, Rendi, Zhang, Ruochen, Diandaru, Ryandito, Cahyawijaya, Samuel, Góngora, Santiago, Jeong, Soyeong, Purkayastha, Sukannya, Kuribayashi, Tatsuki, Clifford, Teresa, Jayakumar, Thanmay, Torrent, Tiago Timponi, Ehsan, Toqeer, Araujo, Vladimir, Kementchedjhieva, Yova, Burzo, Zara, Lim, Zheng Wei, Yong, Zheng Xin, Ignat, Oana, Nwatu, Joan, Mihalcea, Rada, Solorio, Thamar, Aji, Alham Fikri
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual and textual data. However, most of the current VQA
Externí odkaz:
http://arxiv.org/abs/2406.05967
Autor:
Chimoto, Everlyn Asiko, Gala, Jay, Ahia, Orevaoghene, Kreutzer, Julia, Bassett, Bruce A., Hooker, Sara
Neural Machine Translation models are extremely data and compute-hungry. However, not all data points contribute equally to model training and generalization. Data pruning to remove the low-value data points has the benefit of drastically reducing th
Externí odkaz:
http://arxiv.org/abs/2405.19462
Despite recent advances in large language models, building dependable and deployable NLP models typically requires abundant, high-quality training data. However, task-specific data is not available for many use cases, and manually curating task-speci
Externí odkaz:
http://arxiv.org/abs/2404.14361
With the increasing use of multicore platforms to realize mixed-criticality systems, understanding the underlying shared resources, such as the memory hierarchy shared among cores, and achieving isolation between co-executing tasks running on the sam
Externí odkaz:
http://arxiv.org/abs/2404.01910
Autor:
Mincigrucci, R., Paltanin, E., Pelli-Cresi, J. -S., Gala, F., Pontecorvo, E., Foglia, L., De Angelis, D., Fainozzi, D., Gessini, A., Molina, D. S. P., Stranik, O., Wechsler, F., Heintzmann, R., Ruocco, G., Bencivenga, F., Masciovecchio, C.
The relentless pursuit of understanding matter at ever-finer scales has pushed optical microscopy to surpass the diffraction limit and produced the super-resolution microscopy which enables visualizing structures shorter than the wavelength of light.
Externí odkaz:
http://arxiv.org/abs/2403.19382
The strength of modern large-scale neural networks lies in their ability to efficiently adapt to new tasks with few examples. Although extensive research has investigated the transferability of Vision Transformers (ViTs) to various downstream tasks u
Externí odkaz:
http://arxiv.org/abs/2403.10696