Zobrazeno 1 - 10
of 1 147
pro vyhledávání: '"A. Vandierendonck"'
Model Inversion (MI) is a type of privacy violation that focuses on reconstructing private training data through abusive exploitation of machine learning models. To defend against MI attacks, state-of-the-art (SOTA) MI defense methods rely on regular
Externí odkaz:
http://arxiv.org/abs/2409.01062
Autor:
Arif, Kazi Hasan Ibn, Yoon, JinYi, Nikolopoulos, Dimitrios S., Vandierendonck, Hans, John, Deepu, Ji, Bo
High-resolution Vision-Language Models (VLMs) have been widely used in multimodal tasks to enhance accuracy by preserving detailed image information. However, these models often generate excessive visual tokens due to encoding multiple partitions of
Externí odkaz:
http://arxiv.org/abs/2408.10945
Autor:
Abreu, Y., Amhis, Y., Arnold, L., Beaumont, W., Bolognino, I., Bongrand, M., Boursette, D., Buridon, V., Chanal, H., Coupé, B., Crochet, P., Cussans, D., D'Hondt, J., Durand, D., Fallot, M., Galbinski, D., Gallego, S., Ghys, L., Giot, L., Graves, K., Guillon, B., Hayashida, S., Henaff, D., Hosseini, B., Kalcheva, S., Kalousis, L. N., Keloth, R., Koch, L., Labare, M., Lehaut, G., Manley, S., Manzanillas, L., Mermans, J., Michiels, I., Monteil, S., Moortgat, C., Newbold, D., Pestel, V., Petridis, K., Piñera, I., de Roeck, A., Roy, N., Ryckbosch, D., Ryder, N., Saunders, D., Schune, M. H., Settimo, M., Sfar, H. Rejeb, Simard, L., Vacheret, A., Van Dyck, S., Van Mulders, P., Van Remortel, N., Vandierendonck, G., Vercaemer, S., Verstraeten, M., Viaud, B., Weber, A., Yeresko, M., Yermia, F.
In this letter we report the first scientific result based on antineutrinos emitted from the BR2 reactor at SCK CEN. The SoLid experiment uses a novel type of highly granular detector whose basic detection unit combines two scintillators, PVT and 6Li
Externí odkaz:
http://arxiv.org/abs/2407.14382
Autor:
Esfahani, Mohsen Koohi, D'Antonio, Marco, Tauhidi, Syed Ibtisam, Mai, Thai Son, Vandierendonck, Hans
Comprehensive evaluation is one of the basis of experimental science. In High-Performance Graph Processing, a thorough evaluation of contributions becomes more achievable by supporting common input formats over different frameworks. However, each fra
Externí odkaz:
http://arxiv.org/abs/2404.19735
Autor:
Esfahani, Mohsen Koohi, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna, Sebastiano
Progress in High-Performance Computing in general, and High-Performance Graph Processing in particular, is highly dependent on the availability of publicly-accessible, relevant, and realistic data sets. To ensure continuation of this progress, we (i)
Externí odkaz:
http://arxiv.org/abs/2308.16744
This paper analyzes the effects of dynamically varying video contents and detection latency on the real-time detection accuracy of a detector and proposes a new run-time accuracy variation model, ROMA, based on the findings from the analysis. ROMA is
Externí odkaz:
http://arxiv.org/abs/2210.16083
Autor:
Abreu, Y., Amhis, Y., Arnold, L., Barber, G., Beaumont, W., Binet, S., Bolognino, I., Bongrand, M., Borg, J., Boursette, D., Buridon, V., Castle, B.C., Chanal, H., Clark, K., Coupé, B., Crochet, P., Cussans, D., De Roeck, A., Durand, D., Durkin, T., Fallot, M., Galbinski, D., Gallego, S., Ghys, L., Giot, L., Graves, K., Guillon, B., Henaff, D., Hosseini, B., Jenzer, S., Kalcheva, S., Kalousis, L.N., Keloth, R., Koch, L., Labare, M., Lehaut, G., Manley, S., Manzanillas, L., Mermans, J., Michiels, I., Monteil, S., Moortgat, C., Newbold, D., Pestel, V., Petridis, K., Piñera, I., Popescu, L., Roy, N., Ryckbosch, D., Ryder, N., Saunders, D., Schune, M.-H., Rejeb Sfar, H., Simard, L., Vacheret, A., Vandierendonck, G., Van Dyck, S., Van Mulders, P., van Remortel, N., Vercaemer, S., Verstraeten, M., Viaud, B., Weber, A., Yeresko, M., Yermia, F.
Publikováno v:
In Nuclear Inst. and Methods in Physics Research, A September 2024 1066
Publikováno v:
IEEE Access, Vol 12, Pp 5490-5502 (2024)
Many weight quantization approaches were explored to save the communication bandwidth between the clients and the server in federated learning using high-end computing machines. However, there is a lack of weight quantization research for online fede
Externí odkaz:
https://doaj.org/article/d7f3178eb1934215955a42380cb29836
Autor:
Lee, JunKyu, Mukhanov, Lev, Molahosseini, Amir Sabbagh, Minhas, Umar, Hua, Yang, del Rincon, Jesus Martinez, Dichev, Kiril, Hong, Cheol-Ho, Vandierendonck, Hans
Deep learning is pervasive in our daily life, including self-driving cars, virtual assistants, social network services, healthcare services, face recognition, etc. However, deep neural networks demand substantial compute resources during training and
Externí odkaz:
http://arxiv.org/abs/2112.15131
Autor:
Minhas, Umar Ibrahim, Mukhanov, Lev, Karakonstantis, Georgios, Vandierendonck, Hans, Woods, Roger
Machine vision tasks present challenges for resource constrained edge devices, particularly as they execute multiple tasks with variable workloads. A robust approach that can dynamically adapt in runtime while maintaining the maximum quality of servi
Externí odkaz:
http://arxiv.org/abs/2108.12914