Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …

Recent advances in algorithm-hardware co-design for deep neural networks (DNNs) have
demonstrated their potential in automatically designing neural architectures and hardware …

The last decade has witnessed a surge of machine learning (eg, deep learning) research
and applications in many real-world scenarios, such as computer vision, language …

This thesis proposes novel algorithm and hardware optimisation approaches to accelerate
Deep Neural Networks (DNNs), including both Convolutional Neural Networks (CNNs) and …