Efficient Architecture

Efficient architecture research focuses on designing and discovering neural network structures that minimize computational cost while maintaining or improving performance. Current efforts concentrate on developing novel search algorithms (e.g., evolutionary, gradient-based methods), exploring alternative model architectures (e.g., transformers, convolutional networks with specialized components), and leveraging knowledge distillation or other techniques to reduce training time and parameter counts. This work is crucial for deploying AI models on resource-constrained devices and for advancing the broader field of machine learning by enabling more sustainable and accessible AI applications.