9 citations · 9 across the 5 of their papers we have counts for
7 papers
Certified Robustness via Sparse Second-Order Cone Relaxations
Mohammadreza Maleki, Daniel Sadig, Rushendra Sidibomma +3
Certified robustness is critical for deploying neural networks in safety-sensitive settings, but computing exact certificates typically requires solving nonconvex optimization prob…
MEDEM: Multi-Engine DL Accelerator Design Methodology
Fareed Qararyah, Mohammad Ali Maleki, Pedro Trancoso
Multi-engine deep learning (DL) accelerators are becoming increasingly prevalent as they address the heterogeneity and growing complexity of modern DL workloads. To efficiently pro…
CEAR: Certified Ensemble Adversarial Robustness in DNNs
Daniel Sadig, Mohammadreza Maleki, Hamed Karimi +1
Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical applications. State-of-the-art empi…
SISA: A Scale-In Systolic Array for GEMM Acceleration
Luigi Altamura, Alessio Cicero, Mateo Vázquez Maceiras +2
The currently dominant AI/ML workloads, such as Large Language Models (LLMs), rely on the efficient execution of General Matrix-Matrix Multiplication (GEMM) operations. Thus, most…
An Analytical Cost Model for Fast Evaluation of Multiple Compute-Engine CNN Accelerators
Fareed Qararyah, Mohammad Ali Maleki, Pedro Trancoso
Convolutional Neural Networks (CNNs) serve various applications with diverse performance and resource requirements. Model-aware CNN accelerators best address these diverse requirem…
Simulation of Quantum Computers: Review and Acceleration Opportunities
Alessio Cicero, Mohammad Ali Maleki, Muhammad Waqar Azhar +2
Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Neverth…
Fusing Depthwise and Pointwise Convolutions for Efficient Inference on GPUs
Fareed Qararyah, Muhammad Waqar Azhar, Mohammad Ali Maleki +1
Depthwise and pointwise convolutions have fewer parameters and perform fewer operations than standard convolutions. As a result, they have become increasingly used in various compa…