23 citations · 66 across the 11 of their papers we have counts for
11 papers
Deep Reinforcement Learning for Voltage Control and Renewable Accommodation Using Spatial-Temporal Graph Information
Jinhao Li, Ruichang Zhang, Hao Wang +3
Renewable energy resources (RERs) have been increasingly integrated into distribution networks (DNs) for decarbonization. However, the variable nature of RERs introduces uncertaint…
Unlocking the Potential of Federated Learning for Deeper Models
Haolin Wang, Xuefeng Liu, Jianwei Niu +2
Federated learning (FL) is a new paradigm for distributed machine learning that allows a global model to be trained across multiple clients without compromising their privacy. Alth…
A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching
Yangyang Guo, Hao Wang, Lei He +3
An efficient team is essential for the company to successfully complete new projects. To solve the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer p…
Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach
Jinhao Li, Changlong Wang, Hao Wang
Wind energy has been rapidly gaining popularity as a means for combating climate change. However, the variable nature of wind generation can undermine system reliability and lead t…
Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning
Zhuo Wei, Frits de Nijs, Jinhao Li +1
The rapid adoption of residential solar photovoltaics (PV) has resulted in regular overvoltage events, due to correlated reverse power flows. Currently, PV inverters prevent damage…
Deep Reinforcement Learning for Wind and Energy Storage Coordination in Wholesale Energy and Ancillary Service Markets
Jinhao Li, Changlong Wang, Hao Wang
Wind energy has been increasingly adopted to mitigate climate change. However, the variability of wind energy causes wind curtailment, resulting in considerable economic losses for…
Image Quality Assessment with Gradient Siamese Network
Heng Cong, Lingzhi Fu, Rongyu Zhang +4
In this work, we introduce Gradient Siamese Network (GSN) for image quality assessment. The proposed method is skilled in capturing the gradient features between distorted images a…
Learning Diverse Tone Styles for Image Retouching
Haolin Wang, Jiawei Zhang, Ming Liu +2
Image retouching, aiming to regenerate the visually pleasing renditions of given images, is a subjective task where the users are with different aesthetic sensations. Most existing…
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
Wanyu Lin, Hao Lan, Hao Wang +1
This paper proposes a new eXplanation framework, called OrphicX, for generating causal explanations for any graph neural networks (GNNs) based on learned latent causal factors. Spe…
Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information
Jinhao Li, Ruichang Zhang, Hao Wang +3
Renewable energy resources (RERs) have been increasingly integrated into large-scale distributed power systems. Considering uncertainties and voltage fluctuation issues introduced…
Critical Learning Periods in Federated Learning
Gang Yan, Hao Wang, Jian Li
Federated learning (FL) is a popular technique to train machine learning (ML) models with decentralized data. Extensive works have studied the performance of the global model; howe…