200 citations · 217 across the 12 of their papers we have counts for
12 papers
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…
Resource Constrained Neural Networks for 5G Direction-of-Arrival Estimation in Micro-controllers
Piyush Sahoo, Romesh Rajoria, Shivam Chandhok +3
With the introduction of shared spectrum sensing and beam-forming based multi-antenna transceivers, 5G networks demand spectrum sensing to identify opportunities in time, frequency…