Zobrazeno 1 - 10
of 721
pro vyhledávání: '"ATIENZA, DAVID"'
Generating synthetic Electronic Health Records (EHRs) offers significant potential for data augmentation, privacy-preserving data sharing, and improving machine learning model training. We propose a novel tokenization strategy tailored for structured
Externí odkaz:
http://arxiv.org/abs/2411.13428
Efficient deployment of resource-intensive transformers on edge devices necessitates cross-stack optimization. We thus study the interrelation between structured pruning and systolic acceleration, matching the size of pruned blocks with the systolic
Externí odkaz:
http://arxiv.org/abs/2411.10285
Autor:
Samakovlis, Dimitrios, Albini, Stefano, Álvarez, Rubén Rodríguez, Constantinescu, Denisa-Andreea, Schiavone, Pasquale Davide, Peón-Quirós, Miguel, Atienza, David
Breakthroughs in ultra-low-power chip technology are transforming biomedical wearables, making it possible to monitor patients in real time with devices operating on mere {\mu}W. Although many studies have examined the power performance of commercial
Externí odkaz:
http://arxiv.org/abs/2411.09534
Autor:
Albini, Stefano, Orlandic, Lara, Dan, Jonathan, Thevenot, Jérôme, Teijeiro, Tomas, Constantinescu, Denisa Andreea, Atienza, David
Continuous cough monitors can greatly aid doctors in home monitoring and treatment of respiratory diseases. Although many algorithms have been proposed, they still face limitations in data privacy and short-term monitoring. Edge-AI offers a promising
Externí odkaz:
http://arxiv.org/abs/2410.24066
Deep learning time-series processing often relies on convolutional neural networks with overlapping windows. This overlap allows the network to produce an output faster than the window length. However, it introduces additional computations. This work
Externí odkaz:
http://arxiv.org/abs/2408.03223
Autor:
Amirshahi, Alireza, Toosi, Maedeh H., Mohammadi, Siamak, Albini, Stefano, Schiavone, Pasquale Davide, Ansaloni, Giovanni, Aminifar, Amir, Atienza, David
Wearable systems provide continuous health monitoring and can lead to early detection of potential health issues. However, the lifecycle of wearable systems faces several challenges. First, effective model training for new wearable devices requires s
Externí odkaz:
http://arxiv.org/abs/2408.01988
Non-linear activation functions are crucial in Convolutional Neural Networks. However, until now they have not been well described in the frequency domain. In this work, we study the spectral behavior of ReLU, a popular activation function. We use th
Externí odkaz:
http://arxiv.org/abs/2407.16556
Publikováno v:
Parallel Computing, 36(10-11), pp. 572-590, 2010
For the last thirty years, several Dynamic Memory Managers (DMMs) have been proposed. Such DMMs include first fit, best fit, segregated fit and buddy systems. Since the performance, memory usage and energy consumption of each DMM differs, software en
Externí odkaz:
http://arxiv.org/abs/2407.09555
Publikováno v:
Microprocessors and Microsystems, 35(8), pp. 755-765, 2011
For the last thirty years, a large variety of memory allocators have been proposed. Since performance, memory usage and energy consumption of each memory allocator differs, software engineers often face difficult choices in selecting the most suitabl
Externí odkaz:
http://arxiv.org/abs/2406.15776
Autor:
Caon, Michele, Choné, Clément, Schiavone, Pasquale Davide, Levisse, Alexandre, Masera, Guido, Martina, Maurizio, Atienza, David
The widespread adoption of data-centric algorithms, particularly Artificial Intelligence (AI) and Machine Learning (ML), has exposed the limitations of centralized processing infrastructures, driving a shift towards edge computing. This necessitates
Externí odkaz:
http://arxiv.org/abs/2406.14263