papers

Publications (10)

cs.LG2020

Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning

Zhenhui Ye, Yining Chen, Guanghua Song +2

Exploration of the high-dimensional state action space is one of the biggest challenges in Reinforcement Learning (RL), especially in multi-agent domain. We present a novel techniq…

cs.SI2021

How Powerful are Interest Diffusion on Purchasing Prediction: A Case Study of Taocode

Xuanwen Huang, Yang Yang, Ziqiang Cheng +5

A taocode is a kind of specially coded text-link on Taobao(the world's biggest online shopping website), through which users can share messages about products with each other. Anal…

astro-ph.SR2023

Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models

Khalid A. Alobaid, Yasser Abduallah, Jason T. L. Wang +5

Coronal mass ejections (CMEs) are massive solar eruptions, which have a significant impact on Earth. In this paper, we propose a new method, called DeepCME, to estimate two propert…

cs.GR2026

STEP-Parts: Geometric Partitioning of Boundary Representations for Large-Scale CAD Processing

Shen Fan, Mikołaj Kida, Przemyslaw Musialski

Many CAD learning pipelines discretize Boundary Representations (B-Reps) into triangle meshes, discarding analytic surface structure and topological adjacency and thereby weakening…

math.DS2009

Gibbs-like measure for spectrum of a class of one-dimensional Schrödinger operator with Sturm potentials

Shen Fan, Qing-Hui Liu, Zhi-Ying Wen

Let be an irrational, and the continued fraction expansion of . Let be the one-dimensional Schrödinger operator with Sturm potential…

cs.SI2022

Who is next: rising star prediction via diffusion of user interest in social networks

Xuan Yang, Yang Yang, Jintao Su +5

Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction.…