activity
20202023
most citedMonte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization

10 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023★ 6 cited

Macro Placement by Wire-Mask-Guided Black-Box Optimization

Yunqi Shi, Ke Xue, Lei Song +1

The development of very large-scale integration (VLSI) technology has posed new challenges for electronic design automation (EDA) techniques in chip floorplanning. During this proc…

cs.LG2022★ 10 cited

Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization

Lei Song, Ke Xue, Xiaobin Huang +1

Bayesian optimization (BO) is a class of popular methods for expensive black-box optimization, and has been widely applied to many scenarios. However, BO suffers from the curse of…

cs.NE2022★ 1 cited

Neural Network Pruning by Cooperative Coevolution

Haopu Shang, Jia-Liang Wu, Wenjing Hong +1

Neural network pruning is a popular model compression method which can significantly reduce the computing cost with negligible loss of accuracy. Recently, filters are often pruned…

cs.LG2022

An Adaptive and Scalable ANN-based Model-Order-Reduction Method for Large-Scale TO Designs

Ren Kai Tan, Chao Qian, Dan Xu +1

Topology Optimization (TO) provides a systematic approach for obtaining structure design with optimum performance of interest. However, the process requires numerical evaluation of…

cs.LG2021

An adaptive artificial neural network-based generative design method for layout designs

Chao Qian, Renkai Tan, Wenjing Ye

Layout designs are encountered in a variety of fields. For problems with many design degrees of freedom, efficiency of design methods becomes a major concern. In recent years, mach…

cs.AI2020★ 1 cited

Accelerating gradient-based topology optimization design with dual-model neural networks

Chao Qian, Wenjing Ye

Topology optimization (TO) is a common technique used in free-form designs. However, conventional TO-based design approaches suffer from high computational cost due to the need for…