cfaed Publications
BiKA: Binarized KAN-inspired Neural Network for Efficient Hardware Accelerator Designs
Reference
Yuhao Liu, Salim Ullah, Akash Kumar, "BiKA: Binarized KAN-inspired Neural Network for Efficient Hardware Accelerator Designs", In Proceeding: 2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), pp. 276-276, 2025. [doi]
Bibtex
@INPROCEEDINGS{11008950,
author={Liu, Yuhao and Ullah, Salim and Kumar, Akash},
booktitle={2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)},
title={BiKA: Binarized KAN-inspired Neural Network for Efficient Hardware Accelerator Designs},
year={2025},
volume={},
number={},
pages={276-276},
keywords={Quantization (signal);Neuromorphic engineering;Computational modeling;Approximate computing;Artificial neural networks;Transforms;Complexity theory;Hardware acceleration;Field programmable gate arrays;fpga;hardware accelerator;approximate computing;kolmogorov-arnold network},
doi={10.1109/FCCM62733.2025.00036}}
author={Liu, Yuhao and Ullah, Salim and Kumar, Akash},
booktitle={2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)},
title={BiKA: Binarized KAN-inspired Neural Network for Efficient Hardware Accelerator Designs},
year={2025},
volume={},
number={},
pages={276-276},
keywords={Quantization (signal);Neuromorphic engineering;Computational modeling;Approximate computing;Artificial neural networks;Transforms;Complexity theory;Hardware acceleration;Field programmable gate arrays;fpga;hardware accelerator;approximate computing;kolmogorov-arnold network},
doi={10.1109/FCCM62733.2025.00036}}
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