Zero-centered output refers to the transformation of model outputs so that they have a mean of zero, which can enhance the convergence speed of optimization algorithms by ensuring balanced gradient updates. This technique is particularly useful in neural networks to prevent bias in learning and facilitate smoother and more stable training dynamics.