7 citations · 17 across the 5 of their papers we have counts for
5 papers
On Effective Scheduling of Model-based Reinforcement Learning
Hang Lai, Jian Shen, Weinan Zhang +5
Model-based reinforcement learning has attracted wide attention due to its superior sample efficiency. Despite its impressive success so far, it is still unclear how to appropriate…
MOFA: Modular Factorial Design for Hyperparameter Optimization
Bo Xiong, Yimin Huang, Hanrong Ye +2
This paper presents a novel and lightweight hyperparameter optimization (HPO) method, MOdular FActorial Design (MOFA). MOFA pursues several rounds of HPO, where each round alternat…
AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling
Wenshuo Ma, Tingzhong Tian, Hang Xu +2
Most state-of-the-art object detection systems follow an anchor-based diagram. Anchor boxes are densely proposed over the images and the network is trained to predict the boxes pos…
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization
Yimin Huang, Yujun Li, Hanrong Ye +2
The evaluation of hyperparameters, neural architectures, or data augmentation policies becomes a critical model selection problem in advanced deep learning with a large hyperparame…
Meta-Learning PAC-Bayes Priors in Model Averaging
Yimin Huang, Weiran Huang, Liang Li +1
Nowadays model uncertainty has become one of the most important problems in both academia and industry. In this paper, we mainly consider the scenario in which we have a common mod…