neural architecture search
Automated search for optimal neural network architectures, reducing reliance on manual design by human experts.
1 milestone
Once-for-All: Train One Network and Specialize It for Efficient Deployment
Han Cai, Chuang Gan, Tianhao Chen, and Song Han at MIT published Once-for-All at ICLR 2020, presenting a method to train a single neural network once and then derive specialised sub-networks for diverse hardware platforms without retraining, reducing the computational cost of neural architecture search by orders of magnitude.