149 citations · 591 across the 39 of their papers we have counts for
8 papers · 1 filter
EM-X-DL: Efficient Cross-Device Deep Learning Side-Channel Attack with Noisy EM Signatures
Josef Danial, Debayan Das, Anupam Golder +3
This work presents a Cross-device Deep-Learning based Electromagnetic (EM-X-DL) side-channel analysis (SCA), achieving >90% single-trace attack accuracy on AES-128, even in the pre…
A Survey of FPGA-Based Robotic Computing
Zishen Wan, Bo Yu, Thomas Yuang Li +5
Recent researches on robotics have shown significant improvement, spanning from algorithms, mechanics to hardware architectures. Robotics, including manipulators, legged robots, dr…
Masked Face Recognition for Secure Authentication
Aqeel Anwar, Arijit Raychowdhury
With the recent world-wide COVID-19 pandemic, using face masks have become an important part of our lives. People are encouraged to cover their faces when in public area to avoid t…
Breaking Barriers: Maximizing Array Utilization for Compute In-Memory Fabrics
Brian Crafton, Samuel Spetalnick, Gauthaman Murali +3
Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has fou…
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning
Sihan Zeng, Aqeel Anwar, Thinh Doan +2
We develop a mathematical framework for solving multi-task reinforcement learning (MTRL) problems based on a type of policy gradient method. The goal in MTRL is to learn a common p…
Counting Cards: Exploiting Variance and Data Distributions for Robust Compute In-Memory
Brian Crafton, Samuel Spetalnick, Arijit Raychowdhury
Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has fou…