9 papers
scaleTRIM: Scalable TRuncation-Based Integer Approximate Multiplier with Linearization and Compensation
Ebrahim Farahmand, Mohammad Javad Askarizadeh, Ali Mahani +4
In this paper, we propose a scalable approximate multiplier design, scaleTRIM, that approximates the multiplication operation using fitted linear functions, also referred to as lin…
ESM: A Framework for Building Effective Surrogate Models for Hardware-Aware Neural Architecture Search
Azaz-Ur-Rehman Nasir, Samroz Ahmad Shoaib, Muhammad Abdullah Hanif +1
Hardware-aware Neural Architecture Search (NAS) is one of the most promising techniques for designing efficient Deep Neural Networks (DNNs) for resource-constrained devices. Surrog…
ShrinkBox: Backdoor Attack on Object Detection to Disrupt Collision Avoidance in Machine Learning-based Advanced Driver Assistance Systems
Muhammad Zaeem Shahzad, Muhammad Abdullah Hanif, Bassem Ouni +1
Advanced Driver Assistance Systems (ADAS) significantly enhance road safety by detecting potential collisions and alerting drivers. However, their reliance on expensive sensor tech…
A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks
Farzad Nikfam, Raffaele Casaburi, Alberto Marchisio +2
Machine learning (ML) is widely used today, especially through deep neural networks (DNNs), however, increasing computational load and resource requirements have led to cloud-based…
A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead
Kamila Zaman, Alberto Marchisio, Muhammad Abdullah Hanif +1
Quantum Computing (QC) claims to improve the efficiency of solving complex problems, compared to classical computing. When QC is integrated with Machine Learning (ML), it creates a…
TinyCL: An Efficient Hardware Architecture for Continual Learning on Autonomous Systems
Eugenio Ressa, Alberto Marchisio, Maurizio Martina +2
The Continuous Learning (CL) paradigm consists of continuously evolving the parameters of the Deep Neural Network (DNN) model to progressively learn to perform new tasks without re…