11 citations · 24 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
Coflex: Enhancing HW-NAS with Sparse Gaussian Processes for Efficient and Scalable DNN Accelerator Design
Yinhui Ma, Tomomasa Yamasaki, Zhehui Wang +2
Hardware-Aware Neural Architecture Search (HW-NAS) is an efficient approach to automatically co-optimizing neural network performance and hardware energy efficiency, making it part…
RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection
Tomomasa Yamasaki, Zhehui Wang, Tao Luo +2
Neural Architecture Search (NAS) is an automated technique to design optimal neural network architectures for a specific workload. Conventionally, evaluating candidate networks in…