3 papers
cs.AR2025
Optimizing Neural Networks with Learnable Non-Linear Activation Functions via Lookup-Based FPGA Acceleration
Mengyuan Yin, Benjamin Chen Ming Choong, Chuping Qu +3
Learned activation functions in models like Kolmogorov-Arnold Networks (KANs) outperform fixed-activation architectures in terms of accuracy and interpretability; however, their co…
quant-ph2025
Is Quantum Optimization Ready? An Effort Towards Neural Network Compression using Adiabatic Quantum Computing
Zhehui Wang, Benjamin Chen Ming Choong, Tian Huang +4
Quantum optimization is the most mature quantum computing technology to date, providing a promising approach towards efficiently solving complex combinatorial problems. Methods suc…
cs.ET2025
Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems
Benjamin Chen Ming Choong, Tao Luo, Cheng Liu +3
Deep neural networks generate and process large volumes of data, posing challenges for low-resource embedded systems. In-memory computing has been demonstrated as an efficient comp…