Zobrazeno 1 - 10
of 575
pro vyhledávání: '"Lima, Priscila A"'
Autor:
Nag, Shashank, Bacellar, Alan T. L., Susskind, Zachary, Jha, Anshul, Liberty, Logan, Sivakumar, Aishwarya, John, Eugene B., Kailas, Krishnan, Lima, Priscila M. V., Yadwadkar, Neeraja J., Franca, Felipe M. G., John, Lizy K.
Transformers are set to become ubiquitous with applications ranging from chatbots and educational assistants to visual recognition and remote sensing. However, their increasing computational and memory demands is resulting in growing energy consumpti
Externí odkaz:
http://arxiv.org/abs/2411.01818
Autor:
Bacellar, Alan T. L., Susskind, Zachary, Breternitz Jr., Mauricio, John, Eugene, John, Lizy K., Lima, Priscila M. V., França, Felipe M. G.
Publikováno v:
International Conference on Machine Learning (ICML) 2024
We introduce the Differentiable Weightless Neural Network (DWN), a model based on interconnected lookup tables. Training of DWNs is enabled by a novel Extended Finite Difference technique for approximate differentiation of binary values. We propose L
Externí odkaz:
http://arxiv.org/abs/2410.11112
Autor:
Queiroz, Rubens Lacerda, Lima, Cabral, Sampaio, Fabio Ferrentini, Lima, Priscila Machado Vieira
This paper evaluates AI from concrete to Abstract (AIcon2abs), a recently proposed method that enables awareness among the general public on machine learning. Such is possible due to the use of WiSARD, an easily understandable machine learning mechan
Externí odkaz:
http://arxiv.org/abs/2401.07386
Climate change and global warming have been trending topics worldwide since the Eco-92 conference. However, little progress has been made in reducing greenhouse gases (GHGs). The problems and challenges related to emissions are complex and require a
Externí odkaz:
http://arxiv.org/abs/2401.00857
Autor:
Susskind, Zachary, Arora, Aman, Miranda, Igor D. S., Bacellar, Alan T. L., Villon, Luis A. Q., Katopodis, Rafael F., de Araujo, Leandro S., Dutra, Diego L. C., Lima, Priscila M. V., Franca, Felipe M. G., Breternitz Jr., Mauricio, John, Lizy K.
The deployment of AI models on low-power, real-time edge devices requires accelerators for which energy, latency, and area are all first-order concerns. There are many approaches to enabling deep neural networks (DNNs) in this domain, including pruni
Externí odkaz:
http://arxiv.org/abs/2304.10618
Autor:
Lima, Priscila de Morais1,2 (AUTHOR) priscila.de.morais.lima@slu.se, Aronsson, Helena3 (AUTHOR), Strand, Line4 (AUTHOR), Björs, Marie3 (AUTHOR), Pantelopoulos, Athanasios3 (AUTHOR)
Publikováno v:
Acta Agriculturae Scandinavica: Section B, Soil & Plant Science. Dec2024, Vol. 74 Issue 1, p1-17. 17p.
Autor:
Aliahmad, Abdulhamid, Lima, Priscila de Morais, Kjerstadius, Hamse, Simha, Prithvi, Vinnerås, Björn, McConville, Jennifer
Publikováno v:
In Water Research 1 January 2025 268 Part B
Autor:
de Oliveira Bressane Lima, Priscila, van de Kassteele, Jan, Schipper, Maarten, Smorenburg, Naomi, S․ van Rooijen, Martijn, Heijne, Janneke, D․ van Gaalen, Rolina
Publikováno v:
In Computer Methods and Programs in Biomedicine December 2024 257
Autor:
Susskind, Zachary, Arora, Aman, Miranda, Igor Dantas Dos Santos, Villon, Luis Armando Quintanilla, Katopodis, Rafael Fontella, de Araujo, Leandro Santiago, Dutra, Diego Leonel Cadette, Lima, Priscila Machado Vieira, Franca, Felipe Maia Galvao, Breternitz Jr., Mauricio, John, Lizy K.
Weightless Neural Networks (WNNs) are a class of machine learning model which use table lookups to perform inference. This is in contrast with Deep Neural Networks (DNNs), which use multiply-accumulate operations. State-of-the-art WNN architectures h
Externí odkaz:
http://arxiv.org/abs/2203.01479
Autor:
Neto, Antonio Sa Barreto, Farias, Felipe, Mialaret, Marco Aurelio Tomaz, Cartaxo, Bruno, Lima, Priscila Alves, Maciel, Paulo
The increasing usage of smartphones in everyday tasks has been motivated many studies on energy consumption characterization aiming to improve smartphone devices' effectiveness and increase user usage time. In this scenario, it is essential to study
Externí odkaz:
http://arxiv.org/abs/2012.10246