In machine learning, backpropagation[1] is a gradient estimation method commonly used for training a neural network to compute its parameter updates. It is an efficient application of the …

2024年11月2日 · Backpropagation is a powerful algorithm in deep learning, primarily used to train artificial neural networks, particularly feed-forward networks. It works iteratively, minimizing the …

2019年8月8日 · Backpropagation algorithm is probably the most fundamental building block in a neural network. It was first introduced in 1960s and almost 30 years later (1989) popularized …

Backpropagation is a machine learning technique essential to the optimization of artificial neural networks. It facilitates the use of gradient descent algorithms to update network weights, which …

2024年10月23日 · Backpropagation is the neural network training process of feeding error rates back through a neural network to make it more accurate. Here’s what you need to know. Ever …

2023年12月27日 · Backpropagation is a foundational technique in neural network training, which is widely appreciated for its straightforward implementation, simplicity in programming, and …

2025年1月13日 · Backpropagation’s efficiency in training networks with millions or billions of parameters makes it a cornerstone in LLM training. Critically, backpropagation can compute …