1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Robustifying and Boosting Training-Free Neural Architecture Search
Zhenfeng He, Yao Shu, Zhongxiang Dai +1
Neural architecture search (NAS) has become a key component of AutoML and a standard tool to automate the design of deep neural networks. Recently, training-free NAS as an emerging…
cs.AI2024★ 1 cited
Localized Zeroth-Order Prompt Optimization
Wenyang Hu, Yao Shu, Zongmin Yu +5
The efficacy of large language models (LLMs) in understanding and generating natural language has aroused a wide interest in developing prompt-based methods to harness the power of…
cs.LG2023★ 1 cited
Quantum Bayesian Optimization
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma +3
Kernelized bandits, also known as Bayesian optimization (BO), has been a prevalent method for optimizing complicated black-box reward functions. Various BO algorithms have been the…