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Tatsukichi Shibuya

3 accepted papers

2025

Binary Stochastic Flip Optimization for Training Binary Neural Networks

ICASSP 2025accepted

For deploying deep neural networks on edge devices with limited resources, binary neural networks (BNNs) have attracted significant attention, due to their computational and memory efficiency. However, once a neural network is binarized, finetuning it on edge devices becomes challenging because most…

Cited by 0SourceScholar
2024

Efficient Target Propagation by Deriving Analytical Solution

AAAI 2024technical

Exploring biologically plausible algorithms as alternatives to error backpropagation (BP) is a challenging research topic in artificial intelligence. It also provides insights into the brain's learning methods. Recently, when combined with well-designed feedback loss functions such as Local Differen…

Cited by 0SourcePDFScholar
2023

Fixed-Weight Difference Target Propagation

AAAI 2023technical

Target Propagation (TP) is a biologically more plausible algorithm than the error backpropagation (BP) to train deep networks, and improving practicality of TP is an open issue. TP methods require the feedforward and feedback networks to form layer-wise autoencoders for propagating the target value…