2 citations · 3 across the 7 of their papers we have counts for
7 papers
Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping
Boyu Chen, Hanxuan Chen, Jiao He +2
We present a simple yet novel parameterized form of linear mapping to achieves remarkable network compression performance: a pseudo SVD called Ternary SVD (TSVD). Unlike vanilla SV…
Modify Training Directions in Function Space to Reduce Generalization Error
Yi Yu, Wenlian Lu, Boyu Chen
We propose theoretical analyses of a modified natural gradient descent method in the neural network function space based on the eigendecompositions of neural tangent kernel and Fis…
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network
Liang Du, Xiaoqing Ye, Xiao Tan +5
The human brain can effortlessly recognize and localize objects, whereas current 3D object detection methods based on LiDAR point clouds still report inferior performance for detec…
On a framework of data assimilation for neuronal networks
Wenyong Zhang, Boyu Chen, Jianfeng Feng +1
When handling real-world data modeled by a complex network dynamical system, the number of the parameters is always even much more than the size of the data. Therefore, in many cas…
FedDKD: Federated Learning with Decentralized Knowledge Distillation
Xinjia Li, Boyu Chen, Wenlian Lu
The performance of federated learning in neural networks is generally influenced by the heterogeneity of the data distribution. For a well-performing global model, taking a weighte…
Intelligent Solution System towards Parts Logistics Optimization
Yaoting Huang, Boyu Chen, Wenlian Lu +2
Due to the complication of the presented problem, intelligent algorithms show great power to solve the parts logistics optimization problem related to the vehicle routing problem (…
Meta-Learning with Hessian-Free Approach in Deep Neural Nets Training
Boyu Chen, Wenlian Lu, Ernest Fokoue
Meta-learning is a promising method to achieve efficient training method towards deep neural net and has been attracting increases interests in recent years. But most of the curren…