200 citations · 217 across the 12 of their papers we have counts for
8 papers · 1 filter
OASI: Objective-Aware Surrogate Initialization for Multi-Objective Bayesian Optimization in TinyML Keyword Spotting
Soumen Garai, Danilo Pau, Suman Samui
Voice-triggered interfaces rely on keyword spotting (KWS) models that must operate continuously under strict memory, latency, and energy constraints on microcontroller-class hardwa…
Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks
Idris Zakariyya, Ferheen Ayaz, Mounia Kharbouche-Harrari +4
Reducing the memory footprint of Machine Learning (ML) models, especially Deep Neural Networks (DNNs), is imperative to facilitate their deployment on resource-constrained edge dev…
Biases in Edge Language Models: Detection, Analysis, and Mitigation
Vinamra Sharma, Danilo Pietro Pau, José Cano
The integration of large language models (LLMs) on low-power edge devices such as Raspberry Pi, known as edge language models (ELMs), has introduced opportunities for more personal…
Enhancing Field-Oriented Control of Electric Drives with Tiny Neural Network Optimized for Micro-controllers
Martin Joel Mouk Elele, Danilo Pau, Shixin Zhuang +1
The deployment of neural networks on resource-constrained micro-controllers has gained momentum, driving many advancements in Tiny Neural Networks. This paper introduces a tiny fee…
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Ferheen Ayaz, Idris Zakariyya, José Cano +4
Reducing the memory footprint of Machine Learning (ML) models, particularly Deep Neural Networks (DNNs), is essential to enable their deployment into resource-constrained tiny devi…
MLPerf Tiny Benchmark
Colby Banbury, Vijay Janapa Reddi, Peter Torelli +19
Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications. However, continued progress is limited by the…
Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers
Giulia Crocioni, Giambattista Gruosso, Danilo Pau +3
Nowadays, Neural Networks represent a major expectation for the realization of powerful Deep Learning algorithms, which can determine several physical systems' behaviors and operat…
Pre-trainable Reservoir Computing with Recursive Neural Gas
Luca Carcano, Emanuele Plebani, Danilo Pietro Pau +1
Echo State Networks (ESN) are a class of Recurrent Neural Networks (RNN) that has gained substantial popularity due to their effectiveness, ease of use and potential for compact ha…