41 citations · 42 across the 2 of their papers we have counts for
3 papers
cs.LG2020
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm
Yun Yue, Ming Li, Venkatesh Saligrama +1
We propose a novel and efficient training method for RNNs by iteratively seeking a local minima on the loss surface within a small region, and leverage this directional vector for…
cs.CV2020★ 41 cited
LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
Ce Zheng, Yecheng Lyu, Ming Li +1
Deep learning based LiDAR odometry (LO) estimation attracts increasing research interests in the field of autonomous driving and robotics. Existing works feed consecutive LiDAR fra…
cs.CV2020★ 1 cited
TreeRNN: Topology-Preserving Deep GraphEmbedding and Learning
Yecheng Lyu, Ming Li, Xinming Huang +3
General graphs are difficult for learning due to their irregular structures. Existing works employ message passing along graph edges to extract local patterns using customized grap…