Recent years have witnessed a surge of interest in develo** trustworthy methods to
evaluate the value of data in many real-world applications (eg, collaborative machine …

Zero-cost proxies (ZC proxies) are a recent architecture performance prediction technique
aiming to significantly speed up algorithms for neural architecture search (NAS). Recent …

The wide application of pre-trained models is driving the trend of once-for-all training in one-
shot neural architecture search (NAS). However, training within a huge sample space …

Recently, zero-shot (or training-free) Neural Architecture Search (NAS) approaches have
been proposed to liberate NAS from the expensive training process. The key idea behind …

Training-free network architecture search (NAS) aims to discover high-performing networks
with zero-cost proxies capturing network characteristics related to the final performance …

Physics-Informed Neural Networks (PINNs), which incorporate PDEs as soft constraints,
train with a composite loss function that contains multiple training point types: different types …

Transformers have shown remarkable performance, however, their architecture design is a
time-consuming process that demands expertise and trial-and-error. Thus, it is worthwhile to …

Recent years have witnessed a surging interest in Neural Architecture Search (NAS).
Various algorithms have been proposed to improve the search efficiency and effectiveness …