Weight-sharing neural architecture search: A battle to shrink the optimization gap
Neural architecture search (NAS) has attracted increasing attention. In recent years,
individual search methods have been replaced by weight-sharing search methods for higher …
individual search methods have been replaced by weight-sharing search methods for higher …
Angle-based search space shrinking for neural architecture search
In this work, we present a simple and general search space shrinking method, called Angle-
Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach …
Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach …
Optimizing neural networks through activation function discovery and automatic weight initialization
G Bingham - arXiv preprint arXiv:2304.03374, 2023 - arxiv.org
Automated machine learning (AutoML) methods improve upon existing models by
optimizing various aspects of their design. While present methods focus on hyperparameters …
optimizing various aspects of their design. While present methods focus on hyperparameters …
M²NAS: Joint Neural Architecture Optimization System With Network Transmission
Differentiable neural architecture search (NAS) methods have achieved comparable results
for low search costs and high performance. Existing differentiable methods focus on …
for low search costs and high performance. Existing differentiable methods focus on …