24 citations · 26 across the 6 of their papers we have counts for
8 papers
Time Minimization in Hierarchical Federated Learning
Chang Liu, Terence Jie Chua, Jun Zhao
Federated Learning is a modern decentralized machine learning technique where user equipments perform machine learning tasks locally and then upload the model parameters to a centr…
Open-set Text Recognition via Character-Context Decoupling
Chang Liu, Chun Yang, Xu-Cheng Yin
The open-set text recognition task is an emerging challenge that requires an extra capability to cognize novel characters during evaluation. We argue that a major cause of the limi…
Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees
Wenhan Cao, Jingliang Duan, Shengbo Eben Li +3
This paper proposes a primal-dual framework to learn a stable estimator for linear constrained estimation problems leveraging the moving horizon approach. To avoid the online compu…
Adaptive Online Distributed Optimal Control of Very-Large-Scale Robotic Systems
Pingping Zhu, Chang Liu, Silvia Ferrari
This paper presents an adaptive online distributed optimal control approach that is applicable to optimal planning for very-large-scale robotics systems in highly uncertain environ…
Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection
Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou +4
Arbitrary shape text detection is a challenging task due to the high variety and complexity of scenes texts. In this paper, we propose a novel unified relational reasoning graph ne…
Mixed Reinforcement Learning with Additive Stochastic Uncertainty
Yao Mu, Shengbo Eben Li, Chang Liu +4
Reinforcement learning (RL) methods often rely on massive exploration data to search optimal policies, and suffer from poor sampling efficiency. This paper presents a mixed reinfor…