102 citations · 738 across the 28 of their papers we have counts for
6 papers · 1 filter
MTMD: Multi-Scale Temporal Memory Learning and Efficient Debiasing Framework for Stock Trend Forecasting
Mingjie Wang, Juanxi Tian, Mingze Zhang +2
The endeavor of stock trend forecasting is principally focused on predicting the future trajectory of the stock market, utilizing either manual or technical methodologies to optimi…
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization
Yandi Li, Haobo Gao, Yunxuan Gao +2
Influence Maximization (IM) is a classical combinatorial optimization problem, which can be widely used in mobile networks, social computing, and recommendation systems. It aims at…
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User Heterogeneity
Mingjie Wang, Jianxiong Guo, Weijia Jia
Federated Learning (FL) is a decentralized learning method used to train machine learning algorithms. In FL, a global model iteratively collects the parameters of local models with…
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning
Tiantian Chen, Siwen Yan, Jianxiong Guo +1
Aiming at selecting a small subset of nodes with maximum influence on networks, the Influence Maximization (IM) problem has been extensively studied. Since it is #P-hard to compute…
Composite Community-Aware Diversified Influence Maximization with Efficient Approximation
Jianxiong Guo, Qiufen Ni, Weili Wu +1
Influence Maximization (IM) is a famous topic in mobile networks and social computing, which aims at finding a small subset of users to maximize the influence spread through online…
Graph Representation Learning for Popularity Prediction Problem: A Survey
Tiantian Chen, Jianxiong Guo, Weili Wu
The online social platforms, like Twitter, Facebook, LinkedIn and WeChat, have grown really fast in last decade and have been one of the most effective platforms for people to comm…