50 citations · 53 across the 5 of their papers we have counts for
3 papers · 1 filter
Surrogate Benchmarks for Model Merging Optimization
Rio Akizuki, Yuya Kudo, Nozomu Yoshinari +4
Model merging techniques aim to integrate the abilities of multiple models into a single model. Most model merging techniques have hyperparameters, and their setting affects the pe…
NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters
Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa
The benchmark datasets for neural architecture search (NAS) have been developed to alleviate the computationally expensive evaluation process and ensure a fair comparison. Recent N…
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari +3
High sensitivity of neural architecture search (NAS) methods against their input such as step-size (i.e., learning rate) and search space prevents practitioners from applying them…