103 citations · 310 across the 23 of their papers we have counts for
6 papers · 1 filter
FedDAR: Federated Domain-Aware Representation Learning
Aoxiao Zhong, Hao He, Zhaolin Ren +2
Cross-silo Federated learning (FL) has become a promising tool in machine learning applications for healthcare. It allows hospitals/institutions to train models with sufficient dat…
PyPose: A Library for Robot Learning with Physics-based Optimization
Chen Wang, Dasong Gao, Kuan Xu +34
Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physic…
DETRs with Hybrid Matching
Ding Jia, Yuhui Yuan, Haodi He +6
One-to-one set matching is a key design for DETR to establish its end-to-end capability, so that object detection does not require a hand-crafted NMS (non-maximum suppression) to r…
RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation
Haodi He, Yuhui Yuan, Xiangyu Yue +1
The segmentation task has traditionally been formulated as a complete-label pixel classification task to predict a class for each pixel from a fixed number of predefined semantic c…
Controlling Directions Orthogonal to a Classifier
Yilun Xu, Hao He, Tianxiao Shen +1
We propose to identify directions invariant to a given classifier so that these directions can be controlled in tasks such as style transfer. While orthogonal decomposition is dire…
EFMVFL: An Efficient and Flexible Multi-party Vertical Federated Learning without a Third Party
Yimin Huang, Xinyu Feng, Wanwan Wang +3
Federated learning allows multiple participants to conduct joint modeling without disclosing their local data. Vertical federated learning (VFL) handles the situation where partici…