activity
20202022
most citedPrivacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain

155 citations · 277 across the 11 of their papers we have counts for

collaborators
Showing 2020Show all

8 papers · 1 filter

q-fin.MF2020

Asset Allocation via Machine Learning and Applications to Equity Portfolio Management

Qing Yang, Zhenning Hong, Ruyan Tian +2

In this paper, we document a novel machine learning based bottom-up approach for static and dynamic portfolio optimization on, potentially, a large number of assets. The methodolog…

eess.SY2020★ 71 cited

Blockchain-Empowered Socially Optimal Transactive Energy System: Framework and Implementation

Qing Yang, Hao Wang

Transactive energy plays a key role in the operation and energy management of future power systems. However, the conventional operational mechanism, which follows a centralized des…

eess.SY2020★ 6 cited

Cooperative Energy Management of HVAC via Transactive Energy

Qing Yang, Hao Wang

Heating, Ventilation, and Air Conditioning (HVAC) energy consumption accounts for a significant part of the total energy consumption of buildings and households. The ubiquitous ado…

cs.NI2020★ 2 cited

Ethna: Analyzing the Underlying Peer-to-Peer Network of the Ethereum Blockchain

Taotao Wang, Chonghe Zhao, Qing Yang +2

The peer-to-peer (P2P) network of blockchain used to transport its transactions and blocks has a high impact on the efficiency and security of the system. The P2P network topologie…

cs.CV2020

CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles

Jingda Guo, Dominic Carrillo, Sihai Tang +6

To reduce the amount of transmitted data, feature map based fusion is recently proposed as a practical solution to cooperative 3D object detection by autonomous vehicles. The preci…

cs.CV2020★ 7 cited

DCANet: Learning Connected Attentions for Convolutional Neural Networks

Xu Ma, Jingda Guo, Sihai Tang +4

While self-attention mechanism has shown promising results for many vision tasks, it only considers the current features at a time. We show that such a manner cannot take full adva…