35 citations · 43 across the 5 of their papers we have counts for
9 papers
Federated Class-Incremental Learning
Jiahua Dong, Lixu Wang, Zhen Fang +4
Federated learning (FL) has attracted growing attention via data-private collaborative training on decentralized clients. However, most existing methods unrealistically assume obje…
Learning-based Framework for Sensor Fault-Tolerant Building HVAC Control with Model-assisted Learning
Shichao Xu, Yangyang Fu, Yixuan Wang +2
As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort a…
Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation
Yixuan Wang, Chao Huang, Zhilu Wang +3
Neural networks are being increasingly applied to control and decision-making for learning-enabled cyber-physical systems (LE-CPSs). They have shown promising performance without r…
Weak Adaptation Learning -- Addressing Cross-domain Data Insufficiency with Weak Annotator
Shichao Xu, Lixu Wang, Yixuan Wang +1
Data quantity and quality are crucial factors for data-driven learning methods. In some target problem domains, there are not many data samples available, which could significantly…
Addressing Class Imbalance in Federated Learning
Lixu Wang, Shichao Xu, Xiao Wang +1
Federated learning (FL) is a promising approach for training decentralized data located on local client devices while improving efficiency and privacy. However, the distribution an…
One for Many: Transfer Learning for Building HVAC Control
Shichao Xu, Yixuan Wang, Yanzhi Wang +2
The design of building heating, ventilation, and air conditioning (HVAC) system is critically important, as it accounts for around half of building energy consumption and directly…