33 citations · 38 across the 12 of their papers we have counts for
8 papers · 1 filter
SAMP-HDRL: Segmented Allocation with Momentum-Adjusted Utility for Multi-agent Portfolio Management via Hierarchical Deep Reinforcement Learning
Xiaotian Ren, Nuerxiati Abudurexiti, Zhengyong Jiang +3
Portfolio optimization in non-stationary markets is challenging due to regime shifts, dynamic correlations, and the limited interpretability of deep reinforcement learning (DRL) po…
Silhouette-to-Contour Registration: Aligning Intraoral Scan Models with Cephalometric Radiographs
Yiyi Miao, Taoyu Wu, Ji Jiang +6
Reliable 3D-2D alignment between intraoral scan (IOS) models and lateral cephalometric radiographs is critical for orthodontic diagnosis, yet conventional intensity-driven registra…
Dental3R: Geometry-Aware Pairing for Intraoral 3D Reconstruction from Sparse-View Photographs
Yiyi Miao, Taoyu Wu, Tong Chen +6
Intraoral 3D reconstruction is fundamental to digital orthodontics, yet conventional methods like intraoral scanning are inaccessible for remote tele-orthodontics, which typically…
DentalSplat: Dental Occlusion Novel View Synthesis from Sparse Intra-Oral Photographs
Yiyi Miao, Taoyu Wu, Tong Chen +6
In orthodontic treatment, particularly within telemedicine contexts, observing patients' dental occlusion from multiple viewpoints facilitates timely clinical decision-making. Rece…
Factor-MCLS: Multi-agent learning system with reward factor matrix and multi-critic framework for dynamic portfolio optimization
Ruoyu Sun, Angelos Stefanidis, Zhengyong Jiang +1
Typical deep reinforcement learning (DRL) agents for dynamic portfolio optimization learn the factors influencing portfolio return and risk by analyzing the output values of the re…
MSWAL: 3D Multi-class Segmentation of Whole Abdominal Lesions Dataset
Zhaodong Wu, Qiaochu Zhao, Ming Hu +13
With the significantly increasing incidence and prevalence of abdominal diseases, there is a need to embrace greater use of new innovations and technology for the diagnosis and tre…
MTS: A Deep Reinforcement Learning Portfolio Management Framework with Time-Awareness and Short-Selling
Fengchen Gu, Zhengyong Jiang, Ángel F. García-Fernández +3
Portfolio management remains a crucial challenge in finance, with traditional methods often falling short in complex and volatile market environments. While deep reinforcement appr…
A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning
Ruoyu Sun, Yue Xi, Angelos Stefanidis +2
Deep Reinforcement Learning (DRL) has been extensively used to address portfolio optimization problems. The DRL agents acquire knowledge and make decisions through unsupervised int…