3 papers
stat.ML2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso
Danru Xu, Erdun Gao, Wei Huang +3
Learning the underlying Bayesian Networks (BNs), represented by directed acyclic graphs (DAGs), of the concerned events from purely-observational data is a crucial part of evidenti…
cs.LG2022
Lipschitz Continuity Retained Binary Neural Network
Yuzhang Shang, Dan Xu, Bin Duan +3
Relying on the premise that the performance of a binary neural network can be largely restored with eliminated quantization error between full-precision weight vectors and their co…
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…