Zobrazeno 1 - 10
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pro vyhledávání: '"Esteves P"'
A level graph is the data of a pair $(G,\pi)$ consisting of a finite graph $G$ and an ordered partition $\pi$ on the set of vertices of $G$. To each level graph on $n$ vertices we associate a polytope in $\mathbb R^n$ called its residue polytope. We
Externí odkaz:
http://arxiv.org/abs/2410.13554
We describe the limits of canonical series along families of curves degenerating to a nodal curve which is general for its topology, in the weak sense that the branches over nodes on each of its components are in general position. We define a fan str
Externí odkaz:
http://arxiv.org/abs/2410.13543
Autor:
Terrazas-Chavira, Gabriela Alejandra, Enriquez, Lauro Manuel Espino, Villalobos, Raúl Hiram Frescas, Domínguez, Carlos Baudel Manjarrez, Esteves, Hazel Eugenia Hoffmann
The pepenaactivity is part of the informal sector, characterized by precariousness and social invisibility; however, it is a key element in the recycling production chain, providing an economic income for many people. In the city of Chihuahua, this a
Externí odkaz:
http://arxiv.org/abs/2410.05283
A long-standing challenge is the design of chips resilient to faults and glitches. Both fine-grained gate diversity and coarse-grained modular redundancy have been used in the past. However, these approaches have not been well-studied under other thr
Externí odkaz:
http://arxiv.org/abs/2409.02553
Publikováno v:
Neurocomputing, 2024
Curvilinear structures are present in various fields in image processing such as blood vessels in medical imaging or roads in remote sensing. Their detection is crucial for many applications. In this article, we propose an unsupervised plug-and-play
Externí odkaz:
http://arxiv.org/abs/2408.12943
This paper presents a sociotechnical vision for managing personal data, including cookies, within Web browsers. We first present our vision for a future of semi-automated data governance on the Web, using policy languages to describe data terms of us
Externí odkaz:
http://arxiv.org/abs/2408.09071
Autor:
Bhardwaj, Kartikeya, Pandey, Nilesh Prasad, Priyadarshi, Sweta, Ganapathy, Viswanath, Esteves, Rafael, Kadambi, Shreya, Borse, Shubhankar, Whatmough, Paul, Garrepalli, Risheek, Van Baalen, Mart, Teague, Harris, Nagel, Markus
In this paper, we propose Sparse High Rank Adapters (SHiRA) that directly finetune 1-2% of the base model weights while leaving others unchanged, thus, resulting in a highly sparse adapter. This high sparsity incurs no inference overhead, enables rap
Externí odkaz:
http://arxiv.org/abs/2407.16712
Autor:
Vasquez, David A. Lazo, Azpiroz, Jaione Tirapu, Ferreira, Rodrigo Neumann Barros, Giro, Ronaldo, Rodriguez, Manuela Fernandes Blanco, Ferreira, Matheus Esteves, Steiner, Mathias B.
Predicting the geometrical evolution of the pore space in geological formations due to fluid-solid interactions has applications in reservoir engineering, oil recovery, and geological storage of carbon dioxide. However, modeling frameworks that combi
Externí odkaz:
http://arxiv.org/abs/2407.04238
Autor:
Gouveia, Inês Pinto, Sheikh, Ahmad T., Shoker, Ali, Fahmy, Suhaib A., Esteves-Verissimo, Paulo
Computational offload to hardware accelerators is gaining traction due to increasing computational demands and efficiency challenges. Programmable hardware, like FPGAs, offers a promising platform in rapidly evolving application areas, with the benef
Externí odkaz:
http://arxiv.org/abs/2406.18117
Autor:
Bhardwaj, Kartikeya, Pandey, Nilesh Prasad, Priyadarshi, Sweta, Ganapathy, Viswanath, Esteves, Rafael, Kadambi, Shreya, Borse, Shubhankar, Whatmough, Paul, Garrepalli, Risheek, Van Baalen, Mart, Teague, Harris, Nagel, Markus
Low Rank Adaptation (LoRA) has gained massive attention in the recent generative AI research. One of the main advantages of LoRA is its ability to be fused with pretrained models adding no overhead during inference. However, from a mobile deployment
Externí odkaz:
http://arxiv.org/abs/2406.13175