vision-model

Although most popular and successful model architectures are designed by human experts, it doesn’t mean we have explored the entire network architecture space and settled down with the best option. We would have a better chance to find the optimal solution if we adopt a systematic and automatic way of learning high-performance model architectures. Automatically learning and evolving network topologies is not a new idea (Stanley & Miikkulainen, 2002). In recent years, the pioneering work by Zoph & Le 2017 and Baker et al....

Debugging deep learning models is a complex and challenging task that requires significant expertise and experience. One of the main reasons for this complexity is that deep learning models involve multiple layers of interconnected nodes, which can make it difficult to pinpoint the source of errors or identify areas where optimization is needed....